Image retrieval with hand drawn draft based on saliency detection

An image retrieval algorithm with hand drawn draft based on saliency detection was proposed and improved. First, salient regions were obtained by an image segmentation method, next region color sparse histograms were computed, and then the histogram was used to compute each region color contrast. The saliency map was improved by an enhancement and suppression method. Salient object was obtained by eliminating low contrast regions and was divided into blocks equally. The average gray value of each block and spatial relationships were feature data for searching. Search process was filling hand draw contour and extracting the feature data and comparing the feature data on disk, then the difference was combined with the spatial weights. Finally the results are sorted, and the pictures are similar if the difference is small. This method can extract good salient objects and obtain accurate retrieval results.