opencv - Impact of converting image to grayscale -


i seeing many machine learning(cnn) tutorial converts read image in grayscale. want know how model understand original color/use color 1 identification criteria if colors converted throughout model creation ?

in consideration colours, there can 2 cases in image processing problem:

  • colours not relevant in object-identification

    in case, converting coloured image grayscale image not matter, because model learning geometry present in image. image-binarization in sharpening image identifying light , dark areas.

  • colours relevant in object-identification

    as might know colours can represented combination of 3 primary rgb colours. each of these r, g , b values vary 0 255 each pixel. however, in gray-scaling, pixel value one-dimensional instead of three-dimensional, , vary 0 255. so, yes, there information loss in terms of actual colours, but, in tradeoff image-sharpness.

    so, there can combined score of r, g, b values @ each point (probably mean (r+g+b)/3), can give number between 0 255, can used representative. that, instead of specific colour information, pixel carries intensity information.

reference: https://en.wikipedia.org/wiki/grayscale


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