Signature verification based on a feature extraction technique

Language: English

Published by GRIN Verlag, GRIN Verlag Okt 2017, 2017

366854154X / 9783668541542

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This item is printed on demand - Print on Demand Titel. Neuware -Master's Thesis from the year 2012 in the subject Technology, grade: 10, , language: English, abstract: In this research we evaluate the use of GLRLM features in offline handwritten signature verification. For each known writer we take a sample of fifteen genuine signatures and extract their GLRLM descriptors. We also used some forged signatures to test the efficiency of our system. We calculate the simple statistical measures and also inter- and intra-class Euclidean distances (measure of variability within the same author) among GLRLM descriptors of the known signatures. The key points Euclidean distances, the image distances and the intra class thresholds are stored as templates. We evaluate use of various intra-class distance thresholds like the mean, standard deviation and range. For each signature claimed to be of the known writers, we extract its GLRLM descriptors and calculate the inter-class distances, that is the Euclidean distances between each of its GLRLM descriptors and those of the known template and image distances between the test signature and members of the genuine sample. The intra-class threshold is compared to the inter-class threshold for the claimed signature to be considered a forgery. A database of 525 genuine signatures and 30 forged signatures consisting of a training set and a test set are used.Books on Demand GmbH, Überseering 33, 22297 Hamburg 64 pp. Englisch.…

Seller Inventory # 9783668541542

Title
Signature verification based on a feature extraction technique
Author
Saba Mushtaq
Publisher
GRIN Verlag, GRIN Verlag Okt 2017
Publication year
2017
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
366854154X
ISBN 13
9783668541542
Item weight
107 grams
Dimensions
210x148x5 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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