DocumentCode
2837524
Title
Off-Line Chinese Signature Verification Segmentation and Feature Extraction
Author
Jun-wen Ji ; Xiao-su Chen
Author_Institution
Coll. of Comput. Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear
2009
fDate
11-13 Dec. 2009
Firstpage
1
Lastpage
4
Abstract
One of the key tasks in off-line Chinese signature verification is how to acquire the segments and its features from the signature image. In this paper we present a new method to solve the problem for random forgeries and simple forgeries. After the signature being binaried, normalized and thinned, the signature image is segmented to some segments and some segment chains. Every segment is represented by a set of seven features, and every segment chain includes a segment chain includes a series of segments. Using the features of segments and considering the impact of the segment chains, a similarity of the signature is computed. A verification rate of 91% has been gained.
Keywords
feature extraction; handwriting recognition; image segmentation; binaried signature; feature extraction; image segmentation; normalized signature; offline Chinese signature verification; random forgery; signature image; simple forgery; thinned signature; Computer science; Educational institutions; Feature extraction; Focusing; Forgery; Handwriting recognition; Image segmentation; Skeleton; Spatial databases; Writing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4507-3
Electronic_ISBN
978-1-4244-4507-3
Type
conf
DOI
10.1109/CISE.2009.5364538
Filename
5364538
Link To Document