Computer Vision. Image math. Copyright 2001 2016 by NHL Hogeschool and Van de Loosdrecht Machine Vision BV All rights reserved



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Computer Vision: Image math and geometric Computer Vision Image math Copyright 2001 2016 by NHL Hogeschool and Van de Loosdrecht Machine Vision BV All rights reserved j.van.de.loosdrecht@nhl.nl, jaap@vdlmv.nl Image math Add (subtract) constant value to all pixels Adjust brightness Add images Extends exposure time (no Schwarzschild effect) Average out distortions and noise Subtract images Background elimination (logarithmic sensor) Motion detection Multiply (divide) image with constant value Adjust brightness Multiply images Selection with use of mask image Divide images Background elimination (linear sensor) 2 Jaap van de Loosdrecht, NHL, vdlmv, j.van.de.loosdrecht@nhl.nl 1

Computer Vision: Image math and geometric Demonstration Image math Open image circles.jl Demo add pixel 80, use LUT = clip Close circles.jl Demo subtract images: motion detection of people in the audience note: camera is necessary! 3 Demonstration Image math usage of mask Demo selection with use of mask image, get grey values of dice 6 open image dice.jl threshold 180 255 labels blobs, analyse pixels -> the six has labelnr 5 threshold 5 5 Fillholes (from segmentation menu) multiply with original image: everything is zero the six has its original values 4 Jaap van de Loosdrecht, NHL, vdlmv, j.van.de.loosdrecht@nhl.nl 2

Computer Vision: Image math and geometric Image math for binary images Binary images: Background = 0 Object = 1 Used for masking operations: And Or Exor Not 5 Demonstration Or operator Demo or: threshold 4 4 on labelled image, in order to select dice two or this image with binary image of the six Note: adding has the same result if blobs do not overlap 6 Jaap van de Loosdrecht, NHL, vdlmv, j.van.de.loosdrecht@nhl.nl 3

Computer Vision: Image math and geometric Image math Abs (= absolute value for all pixels) Invert image Remainder images Min images Max images Mean images Modulo images ModuloPixel image pixel value Power imagex imagey PowerPixel image value 7 Demonstration Image math Demo invert image on circles.jl 8 Jaap van de Loosdrecht, NHL, vdlmv, j.van.de.loosdrecht@nhl.nl 4

Computer Vision: Image math and geometric Exercise using masks Image h1.jl 9 Exercise using masks Use Int16Image h1.jl with has values in range [0..255] a) write a script which changes all pixel with value 255 to 0, all other pixels are not changed b) write a script which changes all pixel with value 100 to 0, all other pixels are not changed c) write a script which changes all pixel with value 100 to 10, all other pixels are not changed d) write a script which replaces all pixels with a specified mask value by a specified new value e) store the result of d on the server and call it with parameters in a new script Tip(e): 03_VisionLab (49-51) 10 Jaap van de Loosdrecht, NHL, vdlmv, j.van.de.loosdrecht@nhl.nl 5

Computer Vision: Image math and geometric Background subtract versus division Purpose: to correct an inhomogeneous illumination Strategies: Logarithmic sensor: subtract images Linear sensor: divide images 11 Demonstration background subtract versus division Open image backsubdiv.jl (or use script backsubdiv.jls) Demonstrate that thresholding is impossible, threshold 100 255 subtract: read e backsubdiv.jl minimumfilter e em EdgeExtend octagon7x7 maximumfilter em back EdgeExtend octagon7x7 copy e sub subtract sub back see result with analyse pixels Threshold 10 255 finds the dots divide: convert e ef FloatImage convert back backf FloatImage // to avoid dividing zero and dividing by zero addpixel ef 0.1 // note: use. and not, addpixel backf 0.1 copy ef divf divide divf backf see result with edit pixels Or use the extendborder operator to generate the background 12 Jaap van de Loosdrecht, NHL, vdlmv, j.van.de.loosdrecht@nhl.nl 6

Computer Vision: Image math and geometric Assignment using masks Complete the scripts: Assignment/Using_masks/A/script.jls Complete the script by setting all pixels of the letters/digits/minus signs to zero, while leaving other pixels unchanged Assignment/Using_masks/B/script.jls (input is result of A) Complete the script by increasing the background of the NL part by 80, while leaving other pixels unchanged Assignment/Using_masks/C/script.jls (input is result of B) Complete the script by changing the entire background to 128 while leaving the other pixels unchanged Tips: See next slide! 13 Hint using masks Look at histogram - Pixel values of the letters range from 0 to 70 - Pixel values of the NL background range from 70 to 130 - Pixel values of the plate values range from 130 to 255 A) B) C) 14 Jaap van de Loosdrecht, NHL, vdlmv, j.van.de.loosdrecht@nhl.nl 7