After spending most of the weekend reading color constancy papers, and finding out things that seem to be quite damaging to my methods i have come across one great big artifact of them. When trying to give my system samples of varying lighting conditions and by artificially creating these as has been done before i have found that the samples although taken under similar conditions with the same camera in virtually the same place in the room have massively different values in the Hue channel thus ruining my results. However i do believe this is due to poor selection of target images, yet it does highlight that if this image had appeared in the live data set rather than the training one it would be misclassified. This is the issue in general with color constancy that human perception does not necesaarily match the machine representation of the image.
The images below are my samples for dark targets of a bottletop. Clearly they all contain something circular but it is hard to see, possibly red etc but not a clear view.
Yet in hue channels we can clearly see that there is a massive difference in these images as the right hand column is completely variant. This i believe to be color constancy or rather the lack of color constancy in effect.
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