hueDistance - computes the distance in a simplified 2d color space. result = hueDistance(col_img,hueParams) Computes the distance of each pixel of the RGB image col_img in a 2d color space (akin to CIE (r,g)) with respect to the color model in hueParams. The result is a 2d array with values between 1 and 0. hueParams is a struct that describes a 2d Gaussian color distribution in the color space with fields: muR - mean value in the CR direction. sigR - standard deviation in the CR direction. muG - mean value in the CG direction. sigG - standard deviation in the CG direction. rho - correlation coefficient between CR and CG. For details see appendix A.4 of Dirk's PhD thesis: Dirk Walther (2006). Interactions of visual attention and object recognition: Computational modeling, algorithms, and psychophysics. Ph.D. thesis. California Institute of Technology. http://resolver.caltech.edu/CaltechETD:etd-03072006-135433. or this book chapter: Dirk B. Walther & Christof Koch (2007). Attention in Hierarchical Models of Object Recognition. In P. Cisek, T. Drew & J. F. Kalaska (Eds.), Progress in Brain Research: Computational Neuroscience: Theoretical insights into brain function. Amsterdam: Elsevier. See also makeHuePyramid, skinHueParams, dataStructures.
0001 % hueDistance - computes the distance in a simplified 2d color space. 0002 % 0003 % result = hueDistance(col_img,hueParams) 0004 % Computes the distance of each pixel of the 0005 % RGB image col_img in a 2d color space (akin to CIE (r,g)) with 0006 % respect to the color model in hueParams. 0007 % The result is a 2d array with values between 1 and 0. 0008 % 0009 % hueParams is a struct that describes a 2d Gaussian 0010 % color distribution in the color space with fields: 0011 % muR - mean value in the CR direction. 0012 % sigR - standard deviation in the CR direction. 0013 % muG - mean value in the CG direction. 0014 % sigG - standard deviation in the CG direction. 0015 % rho - correlation coefficient between CR and CG. 0016 % 0017 % For details see appendix A.4 of Dirk's PhD thesis: 0018 % Dirk Walther (2006). Interactions of visual attention and object recognition: 0019 % Computational modeling, algorithms, and psychophysics. Ph.D. thesis. 0020 % California Institute of Technology. 0021 % http://resolver.caltech.edu/CaltechETD:etd-03072006-135433. 0022 % 0023 % or this book chapter: 0024 % Dirk B. Walther & Christof Koch (2007). Attention in 0025 % Hierarchical Models of Object Recognition. In P. Cisek, 0026 % T. Drew & J. F. Kalaska (Eds.), Progress in Brain Research: 0027 % Computational Neuroscience: Theoretical insights into brain 0028 % function. Amsterdam: Elsevier. 0029 % 0030 % See also makeHuePyramid, skinHueParams, dataStructures. 0031 0032 % This file is part of the SaliencyToolbox - Copyright (C) 2006-2007 0033 % by Dirk B. Walther and the California Institute of Technology. 0034 % See the enclosed LICENSE.TXT document for the license agreement. 0035 % More information about this project is available at: 0036 % http://www.saliencytoolbox.net 0037 0038 function result = hueDistance(col_img,hueParams) 0039 0040 if ~isa(col_img,'double') 0041 col_img = im2double(col_img); 0042 end 0043 0044 r = col_img(:,:,1); 0045 g = col_img(:,:,2); 0046 b = col_img(:,:,3); 0047 int = r + g + b; 0048 0049 cr = safeDivide(r,int) - hueParams.muR; 0050 cg = safeDivide(g,int) - hueParams.muG; 0051 0052 result = exp(-(cr.^2/hueParams.sigR^2/2 + ... 0053 cg.^2/hueParams.sigG^2/2 - ... 0054 cr.*cg * hueParams.rho/hueParams.sigR/hueParams.sigG));