DIGITAL IMAGE PROCESSING AND ANALYSIS
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1 DIGITAL IMAGE PROCESSING AND ANALYSIS Human and Computer Vision Applications with CVIPtools SECOND EDITION SCOTT E UMBAUGH Uffi\ CRC Press Taylor &. Francis Group Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Group, an informa business
2 Contents Preface Acknowledgments Author xv xix xxi Section I Introduction to Digital Image Processing and Analysis 1. Digital Image Processing and Analysis Overview Image Analysis and Computer Vision Image Processing and Human Vision Key Points 12 Exercises 13 References 13 Further Reading Computer Imaging Systems Imaging Systems Overview Image Formation and Sensing Visible Light Imaging Imaging outside the Visible Range of the EM Spectrum Acoustic Imaging Electron Imaging Laser Imaging Computer-Generated Images CVIPtools Software Main Window Image Viewer Analysis Window Enhancement Window Restoration Window Compression Window Utilities Window Help Window Development Tools Image Representation Binary Images Gray-Scale Images Color Images Multispectral Images Digital Image File Formats Key Points 65 v
3 vi Contents Exercises 68 Problems 68 Programming Exercises 70 Supplementary Exercises 70 Supplementary Problems 70 Supplementary Programming Exercises 71 References 72 Further Reading 73 Section II Digital Image Analysis and Computer Vision 3. Introduction to Digital Image Analysis Introduction Overview System Model Preprocessing Region of Interest Image Geometry Arithmetic and Logic Operations Spatial Filters Image Quantization Binary Image Analysis Basic Image Thresholding Connectivity and Labeling Basic Binary Object Features Ill Binary Object Classification Key Points 125 Exercises 129 Problems 129 Programming Exercises 132 Supplementary Exercises 134 Supplementary Problems 134 Supplementary Programming Exercises 135 References 137 Further Reading Segmentation and Edge/Line Detection Introduction and Overview Edge/Line Detection Gradient Operators Compass Masks Advanced Edge Detectors Edges in Color Images Edge Detector Performance Hough Transform CVIPtools Parameters for the Hough Transform Corner Detection 185
4 Contents vii 4.3 Segmentation Region Growing and Shrinking Clustering Techniques Boundary Detection Combined Segmentation Approaches Morphological Filtering Key Points 236 Exercises 245 Problems 245 Programming Exercises 250 Supplementary Exercises 251 Supplementary Problems 251 Supplementary Programming Exercises 254 References 255 Further Reading Discrete Transforms Introduction and Overview Fourier Transform One-Dimensional Discrete Fourier Transform Two-Dimensional Discrete Fourier Transform Fourier Transform Properties Linearity Convolution Translation Modulation Rotation Periodicity Sampling and Aliasing Displaying the Discrete Fourier Spectrum Discrete Cosine Transform Discrete Walsh-Hadamard Transform Discrete Haar Transform Principal Components Transform Filtering Lowpass Filters Highpass Filters Bandpass and Bandreject Filters Discrete Wavelet Transform Key Points 315 Exercises 322 Problems 322 Programming Exercises 329 Supplementary Exercises 330 Supplementary Problems 330 Supplementary Programming Exercises 332 References 333 Further Reading 333
5 6. Feature Analysis and Pattern Classification Introduction and Overview Feature Extraction Shape Features Histogram Features Color Features Spectral Features Texture Features Feature Extraction with CVIPtools Feature Analysis Feature Vectors and Feature Spaces Distance and Similarity Measures Data Preprocessing Pattern Classification Algorithm Development: Training and Testing Methods Classification Algorithms and Methods Cost/Risk Functions and Success Measures Pattern Classification with CVIPtools Key Points 378 Exercises 387 Problems 387 Programming Exercises 391 Supplementary Exercises 395 Supplementary Problems 395 Supplementary Programming Exercises 397 References 398 Further Reading 399 Section HI Digital Image Processing and Human Vision 7. Digital Image Processing and Visual Perception Introduction and Overview Human Visual Perception Human Visual System Spatial Frequency Resolution Brightness Adaptation Temporal Resolution Perception and Illusion Image Fidelity Criteria Objective Fidelity Measures Subjective Fidelity Measures Key Points 432 Exercises 436 Problems 436 Programming Exercises 439 Supplementary Exercises 439 Supplementary Problems 439 Supplementary Programming Exercises 440
6 Contents ix References 441 Further Reading Image Enhancement Introduction and Overview Gray-Scale Modification Mapping Equations Histogram Modification Adaptive Contrast Enhancement Color Image Sharpening Highpass Filtering High Frequency Emphasis Directional Difference Filters Homomorphic Filtering Unsharp Masking Edge Detector-Based Sharpening Algorithms Image Smoothing Frequency Domain Lowpass Filtering Convolution Mask Lowpass Filtering Nonlinear Filtering Key Points 514 Exercises 521 Problems 521 Programming Exercises 527 Supplementary Exercises 529 Supplementary Problems 529 Supplementary Programming Exercises 530 References 531 Further Reading Image Restoration and Reconstruction Introduction and Overview System Model Noise Models Noise Histograms Periodic Noise Estimation of Noise Noise Removal Using Spatial Filters Order Filters Mean Filters Adaptive Filters Degradation Function Spatial Domain: Point Spread Function Frequency Domain: Modulation/Optical Transfer Function Estimation of the Degradation Function 576
7 X Contents 9.5 Frequency Domain Filters Inverse Filter Wiener Filter Constrained Least Squares Filter Geometrie Mean Filters Adaptive Filtering Bandpass, Bandreject, and Notch Filters Practical Considerations Geometrie Transforms Spatial Transforms Gray-Level Interpolation Geometric Restoration Procedure Geometric Restoration with CVIPtools Image Reconstruction Reconstruction Using Backprojections Radon Transform Fourier-Slice Theorem and Direct Fourier Reconstruction Key Points 611 Exercises 624 Problems 624 Programming Exercises 629 Supplementary Exercises 631 Supplementary Problems 631 Supplementary Programming Exercises 633 References 633 Further Reading Image Compression Introduction and Overview Compression System Model Lossless Compression Methods Huff man Coding Run-Length Coding Lempel-Ziv-Welch Coding Arithmetic Coding Lossy Compression Methods Gray-Level Run-Length Coding Block Truncation Coding Vector Quantization Differential Predictive Coding Model-Based and Fractal Compression Transform Coding Hybrid and Wavelet Methods Key Points 696 Exercises 702 Problems 702 Programming Exercises 707
8 Contents xi Supplementary Exercises 708 Supplementary Problems 708 Supplementary Programming Exercises 709 References 710 Further Reading 711 Section IV Programming and Application Development with CVIPtools 11. CVIPlab Introduction to CVIPlab Toolkits, Toolboxes, and Application Libraries Compiling and Linking CVIPlab How to Build the CVIPlab Project with Microsoft's Visual C Mechanics of Adding a Function with Microsoft's Visual C Using CVIPlab in the Programming Exercises with Microsoft's Visual C Using Microsoft's Visual C Image Data and File Structures CVIP Projects Digital Image Analysis and Computer Vision Projects Digital Image Processing and Human Vision Projects Application Development Introduction and Overview CVIP Algorithm Test and Analysis Tool Overview and Capabilities How to Use CVIP-ATAT Running CVIP-ATAT Creating a New Project Inserting Images Inputting an Algorithm Performing an Algorithm Test Run Comparing Images Application Development Example with Fundus Images Introduction and Overview New Algorithm Conclusion CVIP Feature Extraction and Pattern Classification Tool Overview and Capabilities How to Use CVIP-FEPC Running CVIP-FEPC Creating a New Project Entering Classes in CVIP-FEPC Adding Images and Associated Classes 763
9 xii Contents Applying Feature Extraction and Pattern Classification Running the Test Result File Application Development Example with Veterinary Thermographic Images Introduction and Overview Experiments Results Conclusion Skin Lesion Classification Using Relative Color Features Introduction and Project Overview Materials and Methods Image Database Creation of Relative Color Images Segmentation and Morphological Filtering Feature Extraction Lesion and Object Feature Spaces Establishing Statistical Models Experiments and Data Analysis Lesion Feature Space Object Feature Space Conclusions Automatic Segmentation of Blood Vessels in Retinal Images Introduction and Overview Materials and Methods Results Postprocessing with Hough Transform and Edge Linking Conclusion Classification of Land Types from Satellite Images Using Quadratic Discriminant Analysis and Multilayer Perceptrons Introduction and Overview Data Reduction and Feature Extraction Object Classification Results Conclusion Acknowledgments Watershed-Based Approach to Skin Lesion Border Segmentation Introduction Materials and Methods Experiments, Results, and Conclusions Faint Line Defect Detection in Microdisplay (CCD) Elements Introduction and Project Overview Design Methodology Line Detection Algorithm Preprocessing Edge Detection Analysis of the Hough Space Results and Discussion Summary and Conclusion 820
10 Contents xiii 12.9 Melanoma and Seborrheic Keratosis Differentiation Using Texture Features Introduction and Overview Materials and Methods Texture Analysis Experiments Results and Discussion Conclusion Acknowledgments Compression of Color Skin Tumor Images with Vector Quantization Introduction and Project Overview Materials and Methods Compression Schemes Subjective Evaluation of the Images Compression Schemes Preprocessing and Transforms Vector Quantization Postprocessing Results and Analysis Results and Analyses for the Schemes with Compression Ratio 4: Results and Analyses for the Schemes with Compression Ratio 8: Results and Analyses for the Schemes with Compression Ratio 14: Results and Analyses for the Schemes with Compression Ratio 20: Comprehensive Analysis of the Four Compression Ratios Conclusions and Future Work Acknowledgments 851 References CVIPtools C Function Libraries Introduction and Overview Arithmetic and Logic Library: ArithLogic.lib 855 Arithlogic Library Function Prototypes Band Image Library: Band.lib Color Image Library: Color.lib 856 Color Library Function Prototypes Compression Library: Compression.lib 857 Compression Library Function Prototypes Conversion Library: Conversion.lib 861 Conversion Library Function Prototypes Display Library: Display.lib Feature Extraction Library: Feature.lib 864 Feature Library Function Prototypes Geometry Library: Geometry.lib 867 Geometry Library Function Prototypes 867
11 xiv Contents Histogram Library: Histogram.lib 870 Histogram Library Function Prototypes Image Library: Image.lib Data Mapping Library: Mapping.lib Morphological Library: Morphological.lib 873 Morphological Library Function Prototypes Noise Library: Noise.lib 875 Noise Library Function Prototypes Segmentation Library: Segmentation.lib 876 Segmentation Library Function Prototypes Spatial Filter Library: SpatialFilter.lib 878 Spatial Filter Library Function Prototypes Transform Library: Transform.lib 884 Transform Library Function Prototypes Transform Filter Library: TransformFilter.lib 885 Transform Filter Library Function Prototypes 885 Section V Appendices Appendix A: CVIPtools CD 891 Appendix B: Installing and Updating CVIPtools 893 Appendix C: CVIPtools Software Organization 895 Appendix D: CVIPtools С Functions 897 D.l Toolkit Libraries 897 D.2 Toolbox Libraries 902 Appendix E: Common Object Module (COM) Functions: cviptools.dll 911 Appendix F: CVIP Resources 923 Index 927 :
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