hsv

I am creating a hsv histogram from an image like below. - (void)processImageWithHsv:(Mat&)image; { Mat image_hsv; cvtColor(image, image_hsv, CV_BGR2HSV); int hbins = 50, sbins = 60; int histSize[] = {hbins, sbins}; float hranges[] = { 0, 360 }; float sranges[] = { 0, 256 }; const float* ranges[] = { hranges, sranges }; MatND hist; int channels[] = {0, 1}; calcHist( &image_hsv, 1, channels, Mat(), // do not use mask hist, 2, histSize, ranges, true, // the histogram is uniform false ); double maxVal = 0; minMaxLoc(hist, 0, &maxVal, 0, 0); // ???: HOW Convert this information to colour value }

I have written a function which converts an Image from RGB > HSV. However, when I save the new image the only thing I get is a black image. What should I fix to get it solved? Any help is kindly appreciated! My code: def HSVColor(img): if isinstance(img,Image): r,g,b = img.split() Hdat = [] Sdat = [] Vdat = [] for rd,gn,bl in zip(r.getdata(),g.getdata(),b.getdata()) : h,s,v = colorsys.rgb_to_hsv(rd/255.,gn/255.,bl/255.) Hdat.append(int(h*255.)) Sdat.append(int(l*255.)) Vdat.append(int(s*255.)) r.putdata(Hdat) g.putdata(Sdat) b.putdata(Vdat) return Image.merge('RGB',(r,g,b)) else: return None

I am trying to implement some image filters, like polaroid, in iphone. I searched on how to filter an existing UIImage to convert it into a polaroid style and come across this stackoverflow link. Taking the answer there as a starting point, I looped through each pixel of the image, taking RGB values, and converted them to HSV, up to this point I have been successful. So this is what I have done (anyone is free to point any mistakes..) double minRGB(double r, double g, double b){ if (r < g){ if (r < b){ return r; }else { return b; } }else { if (g < b){ return g; }else{ return b; } } } double

My original question I read that to convert a RGB pixel into greyscale RGB, one should use r_new = g_new = b_new = r_old * 0.3 + g_old * 0.59 + b_old * 0.11 I also read, and understand, that g has a higher weighting because the human eye is more sensitive to green. Implementing that, I saw the results were the same as I would get from setting an image to 'greyscale' in an image editor like the Gimp. Before I read this, I imagined that to convert a pixel to greyscale, one would convert it to HSL or HSV, then set the saturation to zero (hence, removing all colour). However, when I did this, I

I have to detect leukocytes cells in an image that contains another blood cells, but the differences can be distinguished through the color of cells, leukocytes have more dense purple color, can be seen in the image below. What color methode I've to use RGB/HSV ? and why ?! sample image: Usually when making decisions like this I just quickly plot the different channels and color spaces and see what I find. It is always better to start with a high quality image than to start with a low one and try to fix it with lots of processing In this specific case I would use HSV. But unlike most color