Edge distance and gray level extraction and orientation invariant transform for Chinese seal recognition

This study finds distances between edge and centroid. The gray levels around edge are also found. These gray levels are used as parameters to conduct pattern recognition. The entire edge gray levels are recorded in a vertical strip. The “vector magnitude invariant transform” technique is used to transfer gray level quantity to an invariant vector magnitude quantity for object-identification. The “vector magnitude invariant transform” technique can solve image rotation problem. Various gray level vertical magnitude quantity strips are generated to cope with image-shifting problem. In this study, 150 comparisons are conducted to find the accuracy-rate of the developed algorithm. Within those 150 comparisons, 15 comparisons are conducted for self-comparison. The other 90 comparisons are conducted for comparisons between two different object images. The algorithm developed in this study can precisely classify seal-print image.