基于机器学习技术的离线签名识别及其伪造检测

Malay Karmakar
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引用次数: 0

摘要

签名验证是当今世界的一个重要方面。已在银行、政府机构、大学(学位验证)等机构进行签名验证。签名可以包括形状、大小、压力、速度和角度。从一群签名中可以找出一个原始签名并加以区分。本文采用harris算法和Surf算法对伪造签名进行检测。我们还讨论了CNN算法。此外,本文还取了真实签名的x-y坐标和伪造签名的x-y坐标,并对两者进行了比较。我们使用Python编程来绘制图形,而图形可以使用Matlab, R, Microsoft Excel和Python来绘制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Offline Signature Recognition and It’s Forgery Detection using Machine Learning Technique
Signature verification is an important aspect in today’s World. Signature has been verified in Banks, Government Agencies, Universities (Degree Verification) etc. Signature can involve in its shape, size, pressure, speed and angle. From a population of Signatures an original signature can be found out and distinguished. In this Paper for Forgery signature Detection we use two algorithm viz.Harris Algorithm and Surf Algorithm. We have also discussed about CNN Algorithm. Moreover in this paper we take the x-y co-ordinate of the real signature and also the x-y co-ordinate of the forged signature and compare among the two. We have used Python Programming for plotting the graphs whereas the graph can be plot using Matlab, R, Microsoft Excel and Python.
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