Comparison of color representations for content-based image retrieval in dermatology.
OBJECTIVE
We compare the effectiveness of 10 different color representations in a content-based image retrieval task for dermatology.


METHODS
As features, we use the average colors of healthy and lesion skin in an image. The extracted features are used to retrieve similar images from a database using a k-nearest-neighbor search and Euclidean distance. The images in the database are divided into four different color categories. We measure the effectiveness of retrieval by the average percentage of retrieved images that belong to the same category as a query image.


RESULTS
We found that the difference of the colors of lesion and healthy skin is a better color descriptor than the pair of these colors. We obtained the best results with the CIE-Lab color representation [75+/-3.8% (95% confidence interval) correct retrieval rate for k=11], followed by CIE-Luv and CIE-Lch.


CONCLUSIONS
CIE-Lab is the most effective color space for content-based image retrieval of dermatological images. The difference of the colors of lesion and healthy skin in an image is a better color descriptor than the pair of these colors.
Bosman
Hedde H W J
HH
Institute of Mathematics and Computing Science, University of Groningen, Groningen, The Netherlands.
Petkov
Nicolai
N
Jonkman
Marcel F
MF
D003116:Color; D016208:Databases, Factual / Q000592:standards*; D003880:Dermatology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000592:standards; D016247:Information Storage and Retrieval / Q000592:standards*; D046609:Libraries, Digital / Q000592:standards*; D012871:Skin Diseases