For each patch, statistical features are computed and embedded in a vector signature. All these signatures will be used in a later image retrieval process. At this stage of the study, none of the features results from segmentation. All are obtained from global measurements on patches computed on

*I*
_{1}
*I*
_{2}
*I*
_{3} and

*YCh*
_{1}
*Ch*
_{2} color components which are derived from the

*RGB* color system according to the following formulas proposed by Ohta [

10] and Carron [

11]:

.

For a given color component whose histogram is called

*H*, the computed features are:

*H*,

*H* reverse sorted, cumulative

*H*, 20%, 40%, 60% and 80% quantiles of cumulative

*H*, meanH, medianH, modeH, SkewnessH, KurtosisH, PearsonModeSkewnessH, that is a total of 13 data. Three of them are themselves vectors of 64 values, but will provide a single feature after distance measurements between two signatures. Definitions of these statistical features can be found in [

12]. With the resulting 5 effective color components (as

*Y*=

*I*
_{1}), 65 distance measures will be taken into account but 1010 values will be stored in the signature vector for each patch. Considering the sparse numerical range of features in signatures, the Kullback-Leibler symmetrical distance has been retained for its ability to manage such values, while remaining simple and fast to implement (compared to Mahalanobis or earth mover's distance for example). The symmetric Kullback-Leibler distance between two vectors

*p*
_{1},

*p*
_{2} of length n is defined by:

.