Triangulation by Ear Clipping
|
|
|
- Gwendolyn Moore
- 9 years ago
- Views:
Transcription
1 Triangulation by Ear Clipping David Eberly Geometric Tools, LLC Copyright c All Rights Reserved. Created: November 18, 2002 Last Modified: August 16, 2015 Contents 1 Introduction 2 2 Ear Clipping 2 3 Polygons with a Hole 7 4 Finding Mutually Visible Vertices 8 5 Polygons with Multiple Holes 10 6 Hierarchies of Polygons 10 1
2 1 Introduction A classic problem in computer graphics is to decompose a simple polygon into a collection of triangles whose vertices are only those of the simple polygon. By definition, a simple polygon is an ordered sequence of n points, V 0 through V n 1. Consecutive vertices are connected by an edge V i, V i+1, 0 i n 2, and an edge V n 1, V 0 connects the first and last points. Each vertex shares exactly two edges. The only place where edges are allowed to intersect are at the vertices. A typical simple polygon is shown in Figure 1. Figure 1. The left polygon is simple. The middle polygon is not simple since vertex 1 is shared by more than two edges. The right polygon is not simple since the edge connecting vertices 1 and 4 is intersected by other edges at points that are not vertices. simple nonsimple nonsimple If a polygon is simple, as you traverse the edges the interior bounded region is always to one side. I assume that the polygon is counterclockwise ordered so that as you traverse the edges, the interior is to your left. The vertex indices in Figure 1 for the simple polygon correspond to a counterclockwise order. The decomposition of a simple polygon into triangles is called a triangulation of the polygon. A fact from computational geometry is that any triangulation of a simple polygon of n vertices always has n 2 triangles. Various algorithms have been developed for triangulation, each characterized by its asymptotic order as n grows without bound. The simplest algorithm, called ear clipping, is the algorithm described in this document. The order is O(n 2 ). Algorithms with better asymptotic order exist, but are more difficult to implement. Horizontal decomposition into trapezoids followed by identification of monotone polygons that are themselves triangulated is an O(n log n) algorithm [1, 3]. An improvement using an incremental randomized algorithm produces an O(n log n) where log n is the iterated logarithm function [5]. This function is effectively a constant for very large n that you would see in practice, so for all practical purposes the randomized method is linear time. An O(n) algorithm exists in theory [2], but is quite complicated. It appears that no implementation is publicly available. 2 Ear Clipping An ear of a polygon is a triangle formed by three consecutive vertices V i0, V i1, and V i2 for which V i1 is a convex vertex (the interior angle at the vertex is smaller than π radians), the line segment from V i0 to V i2 lies completely inside the polygon, and no vertices of the polygon are contained in the triangle other than the three vertices of the triangle. In the computational geometry jargon, the line segment between V i0 and 2
3 V i2 is a diagonal of the polygon. The vertex V i1 is called the ear tip. A triangle consists of a single ear, although you can place the ear tip at any of the three vertices. A polygon of four or more sides always has at least two nonoverlapping ears [4]. This suggests a recursive approach to the triangulation. If you can locate an ear in a polygon with n 4 vertices and remove it, you have a polygon of n 1 vertices and can repeat the process. A straightforward implementation of this will lead to an O(n 3 ) algorithm. With some careful attention to details, the ear clipping can be done in O(n 2 ) time. The first step is to store the polygon as a doubly linked list so that you can quickly remove ear tips. Construction of this list is an O(n) process. The second step is to iterate over the vertices and find the ears. For each vertex V i and corresponding triangle V i 1, V i, V i+1 (indexing is modulo n, so V n = V 0 and V 1 = V n 1 ), test all other vertices to see if any are inside the triangle. If none are inside, you have an ear. If at least one is inside, you do not have an ear. The actual implementation I provide tries to make this somewhat more efficient. It is sufficient to consider only reflex vertices in the triangle containment test. A reflex vertex is one for which the interior angle formed by the two edges sharing it is larger than 180 degrees. A convex vertex is one for which the interior angle is smaller than 180 degrees. The data structure for the polygon maintains four doubly linked lists simultaneously, using an array for storage rather than dynamically allocating and deallocating memory in a standard list data structure. The vertices of the polygon are stored in a cyclical list, the convex vertices are stored in a linear list, the reflex vertices are stored in a linear list, and the ear tips are stored in a cyclical list. Once the initial lists for reflex vertices and ears are constructed, the ears are removed one at a time. If V i is an ear that is removed, then the edge configuration at the adjacent vertices V i 1 and V i+1 can change. If an adjacent vertex is convex, a quick sketch will convince you that it remains convex. If an adjacent vertex is an ear, it does not necessarily remain an ear after V i is removed. If the adjacent vertex is reflex, it is possible that it becomes convex and, possibly, an ear. Thus, after the removal of V i, if an adjacent vertex is convex you must test if it is an ear by iterating over over the reflex vertices and testing for containment in the triangle of that vertex. There are O(n) ears. Each update of an adjacent vertex involves an earness test, a process that is O(n) per update. Thus, the total removal process is O(n 2 ). The following example, using the simple polygon of Figure 1, shows at a high level how the algorithm is structured. The initial list of convex vertices is C = {0, 1, 3, 4, 6, 9}, the initial list of reflex vertices is R = {2, 5, 7, 8}, and the initial list of ears is E = {3, 4, 6, 9}. The ear at vertex 3 is removed, so the first triangle in the triangulation is T 0 = 2, 3, 4. Figure 2 shows the reduced polygon with the new edge drawn in blue. Figure 2. The right polygon shows the ear 2, 3, 4 removed from the left polygon. The adjacent vertex 2 was reflex and still is. The adjacent vertex 4 was an ear and remains so. The reflex list R remains unchanged, but the edge list is now E = {4, 6, 9} (removed vertex 3). 3
4 The ear at vertex 4 is removed. The next triangle in the triangulation is T 1 = 2, 4, 5. Figure 3 shows the reduced polygon with the new edge drawn in blue. Figure 3. The right polygon shows the ear 2, 3, 4 removed from the left polygon. The adjacent vertex 2 was reflex and still is. The adjacent vertex 5 was reflex, but is now convex. It is tested and found to be an ear. The vertex is removed from the reflex list, R = {2, 7, 8}. It is also added to the ear list, E = {5, 6, 9} (added vertex 5, removed vertex 4). The ear at vertex 5 is removed. The next triangle in the triangulation is T 2 = 2, 5, 6. Figure 4 shows the reduced polygon with the new edge drawn in blue. Figure 4. The right polygon shows the ear 2, 5, 6 removed from the left polygon. The adjacent vertex 2 was reflex, but is now convex. Although difficult to tell from the figure, the vertex 7 is inside the triangle 1, 2, 6, so vertex 2 is not an ear. The adjacent vertex 6 was an ear and remains so. The new reflex list is R = {7, 8} (removed vertex 2) and the new ear list is E = {6, 9} (removed vertex 5). The ear at vertex 6 is removed. The next triangle in the triangulation is T 3 = 2, 6, 7. Figure 5 shows the reduced polygon with the new edge drawn in blue. 4
5 Figure 5. The right polygon shows the ear 2, 6, 7 removed from the left polygon. The adjacent vertex 2 was convex and remains so. It was not an ear, but now it becomes one. The adjacent vertex 7 was reflex and remains so. The reflect list R does not change, but the new ear list is E = {9, 2} (added vertex 2, removed vertex 6). The ear list is written this way because the new ear is added first before the old ear is removed. Before removing the old ear, it is still considered to be first in the list (well, the list is cyclical). The remove operation sets the first item to be that next value to the old ear rather than the previous value. The ear at vertex 9 is removed. The next triangle in the triangulation is T 4 = 8, 9, 0. Figure 6 shows the reduced polygon with the new edge drawn in blue. Figure 6. The right polygon shows the ear 8, 9, 0 removed from the left polygon. The adjacent vertex 8 was reflex, but is now convex and in fact an ear. The adjacent vertex 0 was convex and remains so. It was not an ear but has become one. The new reflex list is R = {7} and the new ear list is E = {0, 2, 8} (added 8, added 0, removed 9, the order shown is what the program produces). The ear at vertex 0 is removed. The next triangle in the triangulation is T 5 = 8, 0, 1. Figure 7 shows the reduced polygon with the new edge drawn in blue. 5
6 Figure 7. The right polygon shows the ear 8, 0, 1 removed from the left polygon. Both adjacent vertices 8 and 1 were convex and remain so. Vertex 8 remains an ear and vertex 1 remains not an ear. The reflex list remains unchanged. The new ear list is E = {2, 8} (removed vertex 0). Finally, the ear at vertex 2 is removed. The next triangle in the triangulation is T 6 = 1, 2, 7. Figure 8 shows the reduced polygon with the new edge drawn in blue. Figure 8. The right polygon shows the ear 1, 2, 7 removed from the left polygon. At this time there is no need to update the reflect or ear lists since we detect that only three vertices remain. The last triangle in the triangulation is T 7 = 7, 8, 1. The full triangulation is show in Figure 9. Figure 9. The full triangulation of the original polygon. 6
7 3 Polygons with a Hole The ear-clipping algorithm may also be applied to polygons with holes. First, consider a polygon with one hole, as shown in Figure 10. It consists of an outer polygon and an inner polygon. The ordering of the outer vertices and the inner vertices must be opposite. If the outer vertices are counterclockwise ordered, then the inner vertices must be clockwise ordered. Figure 10. A polygon with a hole. The blue vertices are mutually visible. We can convert this to the topology of a simple polygon by introducing two coincident edges connecting the blue-colored vertices. Figure 11 shows the two new edges, one drawn in blue and one drawn next to it in red. The edges are coincident; drawing them as shown just illustrates there are two edges. Figure 11. The polygon hole is removed by introducing two new edges that cut open the polygon. Small arrows are attached to the edges to show their directions. The mutually visible vertices must be duplicated in the sense that the vertex data structures are distinct. Each such data structure will store whether the vertex is convex or reflex. Even though a duplicated vertex has the same position as the original, one can be convex and the other reflex. For example, the bottom-most blue point has two vertices associated with it, V 11 and V 18. The original vertex was reflex for the outer 7
8 polygon. After duplication, V 11 associated with the red edge is a reflex vertex but V 18 associated with the blue edge is a convex vertex. The original outer polygon has vertices and the original inner polygon has vertices {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14} {15, 16, 17} Vertex V 11 is duplicated to produce V 18 and vertex V 16 is duplicated to produce V 19. The polygon after introducing the two new edges is {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 16, 17, 15, 19, 18, 12, 13, 14} The new polygon may be triangulated by ear clipping. 4 Finding Mutually Visible Vertices Visually, we can see in Figure 10 that vertices V 11 and V 16 are mutually visible. In fact, there are many more such pairs, one vertex from the outer polygon and one vertex from the inner polygon. We need an algorithm that will find a pair of mutually visible vertices. One such algorithm is the following. Search the vertices of the inner polygon to find the one with maximum x-value. In Figure 10, this is V 16. Imagine an observer standing at this this vertex, looking in the positive x-direction. He will see (1) an interior point of an edge or (2) a vertex, an interior point of an edge being the most probable candidate. If a vertex is visible, then we have a mutually visible pair. Consider, though, that the closest visible point in the positive x-direction is an interior edge point, as illustrated in Figure 12. Figure 12. The closest visible point is an interior edge point. Let M be the origin of the ray (in the example, V 16 ). The ray M + t(1, 0) is shown in blue. The closest visible point is shown in red, call this point I. The edge on which the closest point occurs is drawn in green. The endpoint of the edge that has maximum x-value is labeled P. The point P is the candidate for mutual 8
9 visibility with M. The line segment connecting them is drawn in purple. The triangle M, I, P is drawn with an orange interior. In 12, P is indeed visible to M. Generally, it is possible that other edges of the outer polygon cross the line segment M, P, in which case P is not visible to M. Figure 13 shows such a situation. Figure 13. A case where P is not visible to M. The gray color denotes the region between the outer and inner polygons. The orange region is also part of the interior. In 12, the entire interior of triangle M, I, P is part of the outer-inner interior. In 13, the outer polygon cuts into the triangle, so only a subset of the triangle interior is part of the outer-inner interior. Four vertices of the outer polygon occur inside triangle M, I, P. Generally, if vertices occur inside this triangle, at least one must be reflex. And of all such reflex vertices, one must be visible to M. In Figure 13, three reflex vertices of the outer polygon occur inside the triangle. They are labeled A, B, and C. The reflex vertex A is visible to M, because it minimizes the angle θ between (1, 0) and the line segments M, R, where R is any reflex vertex. The algorithm is summarized as: 1. Search the inner polygon for vertex M of maximum x-value. 2. Intersect the ray M + t(1, 0) with all directed edges V i, V i+1 of the outer polygon for which M is to the left of the line containing the edge (M is inside the outer polygon). Let I be the closest visible point to M on this ray. 3. If I is a vertex of the outer polygon, then M and I are mutually visible and the algorithm terminates. 4. Otherwise, I is an interior point of the edge V i, V i+1. Select P to be the endpoint of maximum x-value for this edge. 5. Search the reflex vertices of the outer polygon (not including P if it happens to be reflex). If all of these vertices are strictly outside triangle M, I, P, then M and P are mutually visible and the algorithm terminates. 6. Otherwise, at least one reflex vertex lies in M, I, P. Search for the reflex R that minimizes the angle between (1, 0) and the line segment M, R. Then M and R are mutually visible and the algorithm terminates. It is possible in this step that there are multiple reflex vertices that minimize the angle, 9
10 in which case all of them lie on a ray with M as the origin. Choose the reflex vertex on this ray that is closest to M. 5 Polygons with Multiple Holes A polygon may have multiple holes (inner polygons). The assumptions are that they are all strictly contained by the outer polygon and none of them overlap. Figure 14 shows such a polygon. Figure 14. An outer polygon with two inner polygons. The figure makes it clear that none of the vertices of inner polygon I 1 are visible to the outer polygon vertices. However, some vertices of inner polygon I 0 are visible to outer polygon vertices. Thus, we may use the previously mentioned algorithm to combine the outer polygon and I 0 into a simple polygon. This polygon becomes the new outer polygon and I 1 is combined with it to form yet another simple polygon. This final polygon is triangulated by ear clipping. Given multiple inner polygons, the one containing the vertex of maximum x-value of all inner polygon vertices is the one chosen to combine with the outer polygon. The process is then repeated with the new outer polygon and the remaining inner polygons. 6 Hierarchies of Polygons The inner polygons themselves can contain outer polygons with holes, thus leading to trees of nested polygons. The root of the tree corresponds to the outermost outer polygon. The children of the root are the inner polygons contained in this outer polygon. Each grandchild (if any) is a subtree whose root corresponds to an outer polygon that is strictly contained in the parent inner polygon and whose own children are inner polygons. A tree of polygons may be processed using a breadth-first traversal. Figure 15 shows a tree of nested polygons that has been triangulated using ear clipping. 10
11 Figure 15. A tree of nested polygons (see SampleFoundation/Triangulation). The tree and its nodes are abstractly shown here: outer0 inner0 inner1 outer1 outer2 inner3 inner4 outer3 inner5 inner2 The pseudocode for processing the tree is struct PolygonTree { Polygon p; array<polygontree> children; }; array<triangle> triangles; PolygonTree tree = <some tree of polygons>; queue<polygontree> Q; Q.insertRear(tree); while (not Q.empty()) do 11
12 { PolygonTree outernode = Q.removeFront(); numchildren = outernode.children.quantity(); if (numchildren == 0) { // The outer polygon is a simple polygon with no nested inner // polygons. triangles.append(getearcliptriangles(outernode.p)); } else { // The outer polygon contains inner polygons. for (i = 0; i < numchildren; i++) { PolygonTree innernode = outernode.children[i]; array<polygon> innerpolygons; numgrandchildren = innernode.children.quantity(); for (j = 0; j < numgrandchildren; j++) { innerpolygons.append(innernode.p); Q.insertFront(innerNode.children[j]); } } } } Polygon combined = MakeSimple(outerNode.p,innerPolygons); triangles.append(getearcliptriangles(combined)); The function MakeSimple encapsulates the algorithm described previously for finding two mutually visible vertices for an outer and an inner polygon, and then duplicates them and inserts two new edges to produce a simple polygon. The process is repeated for each inner polygon. The final triangulation is actually postprocessed so that the indices for the duplicated vertices are replaced by indices for the original vertices. This is slightly tricky in that duplicated vertices can themselves be duplicated you need to follow the chains of indices back to their original values. 12
13 References [1] B. Chazelle and J. Incerpi, Triangulation and shape complexity, ACM Trans. on Graphics, vol. 3, pp , [2] B. Chazelle, Triangulating a simple polygon in linear time, Discrete Comput. Geom., vol. 6, pp , [3] A. Fournier and D.Y. Montuno, Triangulating simple polygons and equivalent problems, ACM Trans. on Graphics, vol. 3, pp , [4] G.H. Meisters, Polygons have ears, Amer. Math. Monthly, vol. 82, pp , [5] R. Seidel, A simple and fast incremental randomized algorithm for computing trapezoidal decompositions and for triangulating polygons, Computational Geometry: Theory and Applications, vol. 1, no. 1, pp ,
Computational Geometry. Lecture 1: Introduction and Convex Hulls
Lecture 1: Introduction and convex hulls 1 Geometry: points, lines,... Plane (two-dimensional), R 2 Space (three-dimensional), R 3 Space (higher-dimensional), R d A point in the plane, 3-dimensional space,
Shortest Inspection-Path. Queries in Simple Polygons
Shortest Inspection-Path Queries in Simple Polygons Christian Knauer, Günter Rote B 05-05 April 2005 Shortest Inspection-Path Queries in Simple Polygons Christian Knauer, Günter Rote Institut für Informatik,
Largest Fixed-Aspect, Axis-Aligned Rectangle
Largest Fixed-Aspect, Axis-Aligned Rectangle David Eberly Geometric Tools, LLC http://www.geometrictools.com/ Copyright c 1998-2016. All Rights Reserved. Created: February 21, 2004 Last Modified: February
Arrangements And Duality
Arrangements And Duality 3.1 Introduction 3 Point configurations are tbe most basic structure we study in computational geometry. But what about configurations of more complicated shapes? For example,
Geometry Chapter 1. 1.1 Point (pt) 1.1 Coplanar (1.1) 1.1 Space (1.1) 1.2 Line Segment (seg) 1.2 Measure of a Segment
Geometry Chapter 1 Section Term 1.1 Point (pt) Definition A location. It is drawn as a dot, and named with a capital letter. It has no shape or size. undefined term 1.1 Line A line is made up of points
MATH STUDENT BOOK. 8th Grade Unit 6
MATH STUDENT BOOK 8th Grade Unit 6 Unit 6 Measurement Math 806 Measurement Introduction 3 1. Angle Measures and Circles 5 Classify and Measure Angles 5 Perpendicular and Parallel Lines, Part 1 12 Perpendicular
Graph Theory Problems and Solutions
raph Theory Problems and Solutions Tom Davis [email protected] http://www.geometer.org/mathcircles November, 005 Problems. Prove that the sum of the degrees of the vertices of any finite graph is
Shortest Path Algorithms
Shortest Path Algorithms Jaehyun Park CS 97SI Stanford University June 29, 2015 Outline Cross Product Convex Hull Problem Sweep Line Algorithm Intersecting Half-planes Notes on Binary/Ternary Search Cross
HOLES 5.1. INTRODUCTION
HOLES 5.1. INTRODUCTION One of the major open problems in the field of art gallery theorems is to establish a theorem for polygons with holes. A polygon with holes is a polygon P enclosing several other
Solving Geometric Problems with the Rotating Calipers *
Solving Geometric Problems with the Rotating Calipers * Godfried Toussaint School of Computer Science McGill University Montreal, Quebec, Canada ABSTRACT Shamos [1] recently showed that the diameter of
Constrained Tetrahedral Mesh Generation of Human Organs on Segmented Volume *
Constrained Tetrahedral Mesh Generation of Human Organs on Segmented Volume * Xiaosong Yang 1, Pheng Ann Heng 2, Zesheng Tang 3 1 Department of Computer Science and Technology, Tsinghua University, Beijing
Algebra Geometry Glossary. 90 angle
lgebra Geometry Glossary 1) acute angle an angle less than 90 acute angle 90 angle 2) acute triangle a triangle where all angles are less than 90 3) adjacent angles angles that share a common leg Example:
Catalan Numbers. Thomas A. Dowling, Department of Mathematics, Ohio State Uni- versity.
7 Catalan Numbers Thomas A. Dowling, Department of Mathematics, Ohio State Uni- Author: versity. Prerequisites: The prerequisites for this chapter are recursive definitions, basic counting principles,
INCIDENCE-BETWEENNESS GEOMETRY
INCIDENCE-BETWEENNESS GEOMETRY MATH 410, CSUSM. SPRING 2008. PROFESSOR AITKEN This document covers the geometry that can be developed with just the axioms related to incidence and betweenness. The full
37 Basic Geometric Shapes and Figures
37 Basic Geometric Shapes and Figures In this section we discuss basic geometric shapes and figures such as points, lines, line segments, planes, angles, triangles, and quadrilaterals. The three pillars
Fast Sequential Summation Algorithms Using Augmented Data Structures
Fast Sequential Summation Algorithms Using Augmented Data Structures Vadim Stadnik [email protected] Abstract This paper provides an introduction to the design of augmented data structures that offer
E XPLORING QUADRILATERALS
E XPLORING QUADRILATERALS E 1 Geometry State Goal 9: Use geometric methods to analyze, categorize and draw conclusions about points, lines, planes and space. Statement of Purpose: The activities in this
2.3 WINDOW-TO-VIEWPORT COORDINATE TRANSFORMATION
2.3 WINDOW-TO-VIEWPORT COORDINATE TRANSFORMATION A world-coordinate area selected for display is called a window. An area on a display device to which a window is mapped is called a viewport. The window
Lesson #13 Congruence, Symmetry and Transformations: Translations, Reflections, and Rotations
Math Buddies -Grade 4 13-1 Lesson #13 Congruence, Symmetry and Transformations: Translations, Reflections, and Rotations Goal: Identify congruent and noncongruent figures Recognize the congruence of plane
Cabri Geometry Application User Guide
Cabri Geometry Application User Guide Preview of Geometry... 2 Learning the Basics... 3 Managing File Operations... 12 Setting Application Preferences... 14 Selecting and Moving Objects... 17 Deleting
Chapter 3.1 Angles. Geometry. Objectives: Define what an angle is. Define the parts of an angle.
Chapter 3.1 Angles Define what an angle is. Define the parts of an angle. Recall our definition for a ray. A ray is a line segment with a definite starting point and extends into infinity in only one direction.
SolidWorks Implementation Guides. Sketching Concepts
SolidWorks Implementation Guides Sketching Concepts Sketching in SolidWorks is the basis for creating features. Features are the basis for creating parts, which can be put together into assemblies. Sketch
Line Segment Intersection
Chapter 1 Line Segment Intersection (with material from [1], [3], and [5], pictures are missing) 1.1 Interval case We first think of having n intervals (e.g., the x-range of horizontal line segments) and
ALGEBRA. sequence, term, nth term, consecutive, rule, relationship, generate, predict, continue increase, decrease finite, infinite
ALGEBRA Pupils should be taught to: Generate and describe sequences As outcomes, Year 7 pupils should, for example: Use, read and write, spelling correctly: sequence, term, nth term, consecutive, rule,
Shortcut sets for plane Euclidean networks (Extended abstract) 1
Shortcut sets for plane Euclidean networks (Extended abstract) 1 J. Cáceres a D. Garijo b A. González b A. Márquez b M. L. Puertas a P. Ribeiro c a Departamento de Matemáticas, Universidad de Almería,
Geometry Review Flash Cards
point is like a star in the night sky. However, unlike stars, geometric points have no size. Think of them as being so small that they take up zero amount of space. point may be represented by a dot on
Basic Geometry Review For Trigonometry Students. 16 June 2010 Ventura College Mathematics Department 1
Basic Geometry Review For Trigonometry Students 16 June 2010 Ventura College Mathematics Department 1 Undefined Geometric Terms Point A Line AB Plane ABC 16 June 2010 Ventura College Mathematics Department
Section 1.1. Introduction to R n
The Calculus of Functions of Several Variables Section. Introduction to R n Calculus is the study of functional relationships and how related quantities change with each other. In your first exposure to
Grade 7 & 8 Math Circles Circles, Circles, Circles March 19/20, 2013
Faculty of Mathematics Waterloo, Ontario N2L 3G Introduction Grade 7 & 8 Math Circles Circles, Circles, Circles March 9/20, 203 The circle is a very important shape. In fact of all shapes, the circle is
Definitions, Postulates and Theorems
Definitions, s and s Name: Definitions Complementary Angles Two angles whose measures have a sum of 90 o Supplementary Angles Two angles whose measures have a sum of 180 o A statement that can be proven
1. A student followed the given steps below to complete a construction. Which type of construction is best represented by the steps given above?
1. A student followed the given steps below to complete a construction. Step 1: Place the compass on one endpoint of the line segment. Step 2: Extend the compass from the chosen endpoint so that the width
Mathematics Geometry Unit 1 (SAMPLE)
Review the Geometry sample year-long scope and sequence associated with this unit plan. Mathematics Possible time frame: Unit 1: Introduction to Geometric Concepts, Construction, and Proof 14 days This
Symbol Tables. Introduction
Symbol Tables Introduction A compiler needs to collect and use information about the names appearing in the source program. This information is entered into a data structure called a symbol table. The
Triangle Trigonometry and Circles
Math Objectives Students will understand that trigonometric functions of an angle do not depend on the size of the triangle within which the angle is contained, but rather on the ratios of the sides of
Introduction to the TI-Nspire CX
Introduction to the TI-Nspire CX Activity Overview: In this activity, you will become familiar with the layout of the TI-Nspire CX. Step 1: Locate the Touchpad. The Touchpad is used to navigate the cursor
Approximation of an Open Polygonal Curve with a Minimum Number of Circular Arcs and Biarcs
Approximation of an Open Polygonal Curve with a Minimum Number of Circular Arcs and Biarcs R. L. Scot Drysdale a Günter Rote b,1 Astrid Sturm b,1 a Department of Computer Science, Dartmouth College b Institut
Disjoint Compatible Geometric Matchings
Disjoint Compatible Geometric Matchings Mashhood Ishaque Diane L. Souvaine Csaba D. Tóth Abstract We prove that for every even set of n pairwise disjoint line segments in the plane in general position,
Duplicating Segments and Angles
CONDENSED LESSON 3.1 Duplicating Segments and ngles In this lesson, you Learn what it means to create a geometric construction Duplicate a segment by using a straightedge and a compass and by using patty
Solutions to Exercises, Section 5.1
Instructor s Solutions Manual, Section 5.1 Exercise 1 Solutions to Exercises, Section 5.1 1. Find all numbers t such that ( 1 3,t) is a point on the unit circle. For ( 1 3,t)to be a point on the unit circle
Selected practice exam solutions (part 5, item 2) (MAT 360)
Selected practice exam solutions (part 5, item ) (MAT 360) Harder 8,91,9,94(smaller should be replaced by greater )95,103,109,140,160,(178,179,180,181 this is really one problem),188,193,194,195 8. On
The minimum number of distinct areas of triangles determined by a set of n points in the plane
The minimum number of distinct areas of triangles determined by a set of n points in the plane Rom Pinchasi Israel Institute of Technology, Technion 1 August 6, 007 Abstract We prove a conjecture of Erdős,
Topology and Topological Rules Geometric properties that are maintained in spatial databases
Topology and Topological Rules Geometric properties that are maintained in spatial databases The definition of topology Topology is a term used around GIS that is sometimes confused with the term topography.
Pre-Algebra 2008. Academic Content Standards Grade Eight Ohio. Number, Number Sense and Operations Standard. Number and Number Systems
Academic Content Standards Grade Eight Ohio Pre-Algebra 2008 STANDARDS Number, Number Sense and Operations Standard Number and Number Systems 1. Use scientific notation to express large numbers and small
Angles that are between parallel lines, but on opposite sides of a transversal.
GLOSSARY Appendix A Appendix A: Glossary Acute Angle An angle that measures less than 90. Acute Triangle Alternate Angles A triangle that has three acute angles. Angles that are between parallel lines,
Free Inductive/Logical Test Questions
Free Inductive/Logical Test Questions (With questions and answers) JobTestPrep invites you to a free practice session that represents only some of the materials offered in our online practice packs. Have
Angle - a figure formed by two rays or two line segments with a common endpoint called the vertex of the angle; angles are measured in degrees
Angle - a figure formed by two rays or two line segments with a common endpoint called the vertex of the angle; angles are measured in degrees Apex in a pyramid or cone, the vertex opposite the base; in
Everyday Mathematics GOALS
Copyright Wright Group/McGraw-Hill GOALS The following tables list the Grade-Level Goals organized by Content Strand and Program Goal. Content Strand: NUMBER AND NUMERATION Program Goal: Understand the
A Note on Maximum Independent Sets in Rectangle Intersection Graphs
A Note on Maximum Independent Sets in Rectangle Intersection Graphs Timothy M. Chan School of Computer Science University of Waterloo Waterloo, Ontario N2L 3G1, Canada [email protected] September 12,
Trigonometric Functions and Triangles
Trigonometric Functions and Triangles Dr. Philippe B. Laval Kennesaw STate University August 27, 2010 Abstract This handout defines the trigonometric function of angles and discusses the relationship between
Segmentation of building models from dense 3D point-clouds
Segmentation of building models from dense 3D point-clouds Joachim Bauer, Konrad Karner, Konrad Schindler, Andreas Klaus, Christopher Zach VRVis Research Center for Virtual Reality and Visualization, Institute
Algebra 2 Chapter 1 Vocabulary. identity - A statement that equates two equivalent expressions.
Chapter 1 Vocabulary identity - A statement that equates two equivalent expressions. verbal model- A word equation that represents a real-life problem. algebraic expression - An expression with variables.
Picture Maze Generation by Successive Insertion of Path Segment
1 2 3 Picture Maze Generation by Successive Insertion of Path Segment 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32. ABSTRACT Tomio Kurokawa 1* 1 Aichi Institute of Technology,
Vector storage and access; algorithms in GIS. This is lecture 6
Vector storage and access; algorithms in GIS This is lecture 6 Vector data storage and access Vectors are built from points, line and areas. (x,y) Surface: (x,y,z) Vector data access Access to vector
Euclidean Minimum Spanning Trees Based on Well Separated Pair Decompositions Chaojun Li. Advised by: Dave Mount. May 22, 2014
Euclidean Minimum Spanning Trees Based on Well Separated Pair Decompositions Chaojun Li Advised by: Dave Mount May 22, 2014 1 INTRODUCTION In this report we consider the implementation of an efficient
Scan-Line Fill. Scan-Line Algorithm. Sort by scan line Fill each span vertex order generated by vertex list
Scan-Line Fill Can also fill by maintaining a data structure of all intersections of polygons with scan lines Sort by scan line Fill each span vertex order generated by vertex list desired order Scan-Line
INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS
INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS STEVEN P. LALLEY AND ANDREW NOBEL Abstract. It is shown that there are no consistent decision rules for the hypothesis testing problem
Many algorithms, particularly divide and conquer algorithms, have time complexities which are naturally
Recurrence Relations Many algorithms, particularly divide and conquer algorithms, have time complexities which are naturally modeled by recurrence relations. A recurrence relation is an equation which
Angles and Quadrants. Angle Relationships and Degree Measurement. Chapter 7: Trigonometry
Chapter 7: Trigonometry Trigonometry is the study of angles and how they can be used as a means of indirect measurement, that is, the measurement of a distance where it is not practical or even possible
Topology. Shapefile versus Coverage Views
Topology Defined as the the science and mathematics of relationships used to validate the geometry of vector entities, and for operations such as network tracing and tests of polygon adjacency Longley
GEOMETRY. Constructions OBJECTIVE #: G.CO.12
GEOMETRY Constructions OBJECTIVE #: G.CO.12 OBJECTIVE Make formal geometric constructions with a variety of tools and methods (compass and straightedge, string, reflective devices, paper folding, dynamic
Research Statement. Andrew Suk
Research Statement Andrew Suk 1 Introduction My research interests are combinatorial methods in discrete geometry. In particular, I am interested in extremal problems on geometric objects. My research
Everyday Mathematics CCSS EDITION CCSS EDITION. Content Strand: Number and Numeration
CCSS EDITION Overview of -6 Grade-Level Goals CCSS EDITION Content Strand: Number and Numeration Program Goal: Understand the Meanings, Uses, and Representations of Numbers Content Thread: Rote Counting
SOLVING TRIGONOMETRIC EQUATIONS
Mathematics Revision Guides Solving Trigonometric Equations Page 1 of 17 M.K. HOME TUITION Mathematics Revision Guides Level: AS / A Level AQA : C2 Edexcel: C2 OCR: C2 OCR MEI: C2 SOLVING TRIGONOMETRIC
Session 5 Dissections and Proof
Key Terms for This Session Session 5 Dissections and Proof Previously Introduced midline parallelogram quadrilateral rectangle side-angle-side (SAS) congruence square trapezoid vertex New in This Session
The GeoMedia Fusion Validate Geometry command provides the GUI for detecting geometric anomalies on a single feature.
The GeoMedia Fusion Validate Geometry command provides the GUI for detecting geometric anomalies on a single feature. Below is a discussion of the Standard Advanced Validate Geometry types. Empty Geometry
2. If C is the midpoint of AB and B is the midpoint of AE, can you say that the measure of AC is 1/4 the measure of AE?
MATH 206 - Midterm Exam 2 Practice Exam Solutions 1. Show two rays in the same plane that intersect at more than one point. Rays AB and BA intersect at all points from A to B. 2. If C is the midpoint of
Solutions to Homework 6
Solutions to Homework 6 Debasish Das EECS Department, Northwestern University [email protected] 1 Problem 5.24 We want to find light spanning trees with certain special properties. Given is one example
11.3 Curves, Polygons and Symmetry
11.3 Curves, Polygons and Symmetry Polygons Simple Definition A shape is simple if it doesn t cross itself, except maybe at the endpoints. Closed Definition A shape is closed if the endpoints meet. Polygon
Situation: Proving Quadrilaterals in the Coordinate Plane
Situation: Proving Quadrilaterals in the Coordinate Plane 1 Prepared at the University of Georgia EMAT 6500 Date Last Revised: 07/31/013 Michael Ferra Prompt A teacher in a high school Coordinate Algebra
Chapter 8 Geometry We will discuss following concepts in this chapter.
Mat College Mathematics Updated on Nov 5, 009 Chapter 8 Geometry We will discuss following concepts in this chapter. Two Dimensional Geometry: Straight lines (parallel and perpendicular), Rays, Angles
Data Structures and Algorithms Written Examination
Data Structures and Algorithms Written Examination 22 February 2013 FIRST NAME STUDENT NUMBER LAST NAME SIGNATURE Instructions for students: Write First Name, Last Name, Student Number and Signature where
Chapter 18 Symmetry. Symmetry of Shapes in a Plane 18.1. then unfold
Chapter 18 Symmetry Symmetry is of interest in many areas, for example, art, design in general, and even the study of molecules. This chapter begins with a look at two types of symmetry of two-dimensional
39 Symmetry of Plane Figures
39 Symmetry of Plane Figures In this section, we are interested in the symmetric properties of plane figures. By a symmetry of a plane figure we mean a motion of the plane that moves the figure so that
Baltic Way 1995. Västerås (Sweden), November 12, 1995. Problems and solutions
Baltic Way 995 Västerås (Sweden), November, 995 Problems and solutions. Find all triples (x, y, z) of positive integers satisfying the system of equations { x = (y + z) x 6 = y 6 + z 6 + 3(y + z ). Solution.
1 Symmetries of regular polyhedra
1230, notes 5 1 Symmetries of regular polyhedra Symmetry groups Recall: Group axioms: Suppose that (G, ) is a group and a, b, c are elements of G. Then (i) a b G (ii) (a b) c = a (b c) (iii) There is an
MODERN APPLICATIONS OF PYTHAGORAS S THEOREM
UNIT SIX MODERN APPLICATIONS OF PYTHAGORAS S THEOREM Coordinate Systems 124 Distance Formula 127 Midpoint Formula 131 SUMMARY 134 Exercises 135 UNIT SIX: 124 COORDINATE GEOMETRY Geometry, as presented
Understand the Sketcher workbench of CATIA V5.
Chapter 1 Drawing Sketches in Learning Objectives the Sketcher Workbench-I After completing this chapter you will be able to: Understand the Sketcher workbench of CATIA V5. Start a new file in the Part
2. Select Point B and rotate it by 15 degrees. A new Point B' appears. 3. Drag each of the three points in turn.
In this activity you will use Sketchpad s Iterate command (on the Transform menu) to produce a spiral design. You ll also learn how to use parameters, and how to create animation action buttons for parameters.
Fast approximation of the maximum area convex. subset for star-shaped polygons
Fast approximation of the maximum area convex subset for star-shaped polygons D. Coeurjolly 1 and J.-M. Chassery 2 1 Laboratoire LIRIS, CNRS FRE 2672 Université Claude Bernard Lyon 1, 43, Bd du 11 novembre
Data Structures Fibonacci Heaps, Amortized Analysis
Chapter 4 Data Structures Fibonacci Heaps, Amortized Analysis Algorithm Theory WS 2012/13 Fabian Kuhn Fibonacci Heaps Lacy merge variant of binomial heaps: Do not merge trees as long as possible Structure:
Geometry 1. Unit 3: Perpendicular and Parallel Lines
Geometry 1 Unit 3: Perpendicular and Parallel Lines Geometry 1 Unit 3 3.1 Lines and Angles Lines and Angles Parallel Lines Parallel lines are lines that are coplanar and do not intersect. Some examples
2006 Geometry Form A Page 1
2006 Geometry Form Page 1 1. he hypotenuse of a right triangle is 12" long, and one of the acute angles measures 30 degrees. he length of the shorter leg must be: () 4 3 inches () 6 3 inches () 5 inches
EE602 Algorithms GEOMETRIC INTERSECTION CHAPTER 27
EE602 Algorithms GEOMETRIC INTERSECTION CHAPTER 27 The Problem Given a set of N objects, do any two intersect? Objects could be lines, rectangles, circles, polygons, or other geometric objects Simple to
Geometry Notes PERIMETER AND AREA
Perimeter and Area Page 1 of 57 PERIMETER AND AREA Objectives: After completing this section, you should be able to do the following: Calculate the area of given geometric figures. Calculate the perimeter
Chapter 1. Creating Sketches in. the Sketch Mode-I. Evaluation chapter. Logon to www.cadcim.com for more details. Learning Objectives
Chapter 1 Creating Sketches in Learning Objectives the Sketch Mode-I After completing this chapter you will be able to: Use various tools to create a geometry. Dimension a sketch. Apply constraints to
Lecture 17 : Equivalence and Order Relations DRAFT
CS/Math 240: Introduction to Discrete Mathematics 3/31/2011 Lecture 17 : Equivalence and Order Relations Instructor: Dieter van Melkebeek Scribe: Dalibor Zelený DRAFT Last lecture we introduced the notion
Angle: An angle is the union of two line segments (or two rays) with a common endpoint, called a vertex.
MATH 008: Angles Angle: An angle is the union of two line segents (or two rays) with a coon endpoint, called a vertex. A B C α Adjacent angles: Adjacent angles are two angles that share a vertex, have
CSU Fresno Problem Solving Session. Geometry, 17 March 2012
CSU Fresno Problem Solving Session Problem Solving Sessions website: http://zimmer.csufresno.edu/ mnogin/mfd-prep.html Math Field Day date: Saturday, April 21, 2012 Math Field Day website: http://www.csufresno.edu/math/news
COMMON CORE STATE STANDARDS FOR MATHEMATICS 3-5 DOMAIN PROGRESSIONS
COMMON CORE STATE STANDARDS FOR MATHEMATICS 3-5 DOMAIN PROGRESSIONS Compiled by Dewey Gottlieb, Hawaii Department of Education June 2010 Operations and Algebraic Thinking Represent and solve problems involving
Line Segments, Rays, and Lines
HOME LINK Line Segments, Rays, and Lines Family Note Help your child match each name below with the correct drawing of a line, ray, or line segment. Then observe as your child uses a straightedge to draw
Scaffolding Task: Angle Tangle
Fourth Grade Mathematics Unit Scaffolding Task: Angle Tangle STANDARDS FOR MATHEMATICAL CONTENT MCC4.MD.5. Recognize angles as geometric shapes that are formed wherever two rays share a common endpoint,
Chapter 13: Query Processing. Basic Steps in Query Processing
Chapter 13: Query Processing! Overview! Measures of Query Cost! Selection Operation! Sorting! Join Operation! Other Operations! Evaluation of Expressions 13.1 Basic Steps in Query Processing 1. Parsing
Lesson 2: Circles, Chords, Diameters, and Their Relationships
Circles, Chords, Diameters, and Their Relationships Student Outcomes Identify the relationships between the diameters of a circle and other chords of the circle. Lesson Notes Students are asked to construct
Intersection of Convex Objects: The Method of Separating Axes
Intersection of Convex Objects: The Method of Separating Axes David Eberly Geometric Tools, LLC http://www.geometrictools.com/ Copyright c 1998-2016. All Rights Reserved. Created: January 28, 2001 Last
Math 1B, lecture 5: area and volume
Math B, lecture 5: area and volume Nathan Pflueger 6 September 2 Introduction This lecture and the next will be concerned with the computation of areas of regions in the plane, and volumes of regions in
Final Review Geometry A Fall Semester
Final Review Geometry Fall Semester Multiple Response Identify one or more choices that best complete the statement or answer the question. 1. Which graph shows a triangle and its reflection image over
