Recognition Of Grouping Areas In Trademarks Considering Proximity And Shape Similarity

According to the Gestalt principals, we model features for representing the attraction degree between pairs of image regions, and, grouping areas in trademarks are recognized. This investigation would be used for content-based image retrieval systems from the view of mirroring human perception for trademark images. Depending on variability in human perception for trademark images, the proposed method finds grouping areas considering combinations of the features. We have evaluated the effectiveness of the proposed method on 36 test images of abstract trademarks from the Japan Trademark Registry. Experimental results have shown over 80% in the images have been the same as humans perception.