DocumentCode :
311094
Title :
Signature identification via local association of features
Author :
Han, Ke ; Sethi, Ishwar K.
Author_Institution :
Dept. of Comput. Sci., Wayne State Univ., Detroit, MI, USA
Volume :
1
fYear :
1995
fDate :
14-16 Aug 1995
Firstpage :
187
Abstract :
Establishing the identify of a signature by automatic search through a database of signatures is of interest in several areas. This paper describes a system for this purpose. The proposed identification system uses a set of geometric and topologic features to characterize each signature. By considering the spatial distribution of these features, the system maps each signature into two strings of finite symbols. A local associative indexing scheme is then used on these strings to organize the collection of signatures of known identity. When presented with a signature of unknown identity, the system uses the same indexing scheme to retrieve a candidate set of signatures. A verification process is then carried out to find the best match from the candidate set. The performance of the proposed system has been tested with a moderate database. The results obtained indicate that the proposed system is able to identify signatures with great accuracy even when a part of a signature is missing
Keywords :
authorisation; feature extraction; handwriting recognition; image matching; indexing; search problems; software performance evaluation; visual databases; automatic search; finite symbols; geometric features; image matching; local association of features; local associative indexing; performance; signature database; signature identification; signature verification; spatial distribution; strings; topologic features; Business; Computer science; Focusing; Handwriting recognition; Indexing; Laboratories; Law enforcement; Neural networks; Spatial databases; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
0-8186-7128-9
Type :
conf
DOI :
10.1109/ICDAR.1995.598973
Filename :
598973
Link To Document :
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