An algorithm based on the histogram of edge difference between MS (model seal) and SS (sample seal) was proposed to verify Chinese seal imprints in bank checks. Difference between MS and an elaborate fake SS may be slight, while that between MS and a genuine SS may be not small due to the variety of imprinting conditions. Edge differences wholly reflect geometrical differences between SS and MS. To evaluate similarities between MS and SS, edge difference was quantified as two parameters, the distance between non-overlapped corresponding edges and the length of each piece of non-overlapped seal edges. A histogram on the product of the two parameters is proposed as the input feature vectors of SVM (support vector machine). SS was verified as true or false by Support Vector Machine (SVM). In Experiments, 4810 (2450 genuine and 2360 fake) seal imprints were verified, and the correct recognition rate is 99.42%. Moreover, the classification results can be customized according to the requirements of users. When the false-acceptance error rate and the false-rejection error rate are both required to be close to 0, the rejection rate is about 3%.

Date Published: 30 November 2012
PDF: 10 pages
Proc. SPIE 8558, Optoelectronic Imaging and Multimedia Technology II, 855804 (30 November 2012); doi: 10.1117/12.999529

Published in SPIE Proceedings Vol. 8558:
Optoelectronic Imaging and Multimedia Technology II
Tsutomu Shimura; Guangyu Xu; Linmi Tao; Jesse Zheng, Editor(s)