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Comparison of Statistical Features for Medical Colour Image Classification Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Arabic-Latin Offline Signature Recognition Based on Shape Context Descriptor

Authors : Ahmed M. Omar, Nagia M. Ghanem, Mohamed A. Ismail, Sahar M. Ghanem

Published in: Computer Vision Systems

Publisher: Springer International Publishing

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Abstract

Offline signature recognition is a very difficult task due to normal variability in signatures and the unavailability of dynamic information regarding the pen path. In this paper, a technique for signature recognition is proposed based on shape context that summarizes the global signature features in a rich local descriptor. The proposed system reaches 100 % accuracy but had some scalability problems as a result of the correspondence problem between the queried signature and all the data set signatures. To address the scalability problem of using shape context for signature matching, the proposed method speeds up the matching stage by representing the shape context features as a feature vector and then applies a clustering algorithm to assign signatures to their corresponding classes.

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previous chapter Improving FREAK Descriptor for Image Classification
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Metadata
Title
Arabic-Latin Offline Signature Recognition Based on Shape Context Descriptor
Authors
Ahmed M. Omar
Nagia M. Ghanem
Mohamed A. Ismail
Sahar M. Ghanem
Copyright Year
2015
Book
Computer Vision Systems

Print ISBN: 978-3-319-20903-6

Electronic ISBN: 978-3-319-20904-3

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-20904-3_3

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