使用机器学习技术进行个性预测系统的手写签名生物特征数据分析

S. Gornale, Sathish Kumar, P. Hiremath
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引用次数: 2

摘要

手写签名已被认为是生物识别安全系统中最广泛接受的个人行为特征之一;它包含各种动态和天生的行为特征,如形状和图案,当然可以发现一个人的软特征,如年龄,性别,个性,惯用手等等。一个人的签名或笔迹决定了这个人在书写时的精神状态或性格特征。本文提出了一种基于离线手写签名图像的不同特征的人格预测系统。实验采用监督学习技术进行。结果显示了显著的识别率,并与同类作品相比验证了对最先进技术的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Handwritten Signature Biometric Data Analysis for Personality Prediction System Using Machine Learning Techniques
Handwritten signature has been considered as one of the most widely accepted behavioral personal trait in Biometric security system; and  It contains various dynamic and innate behavioral traits like shapes and patterns which can certainly find a person’s soft characteristics like age, gender, Personality, handedness and many more. Person’s signature or handwriting determines the state of the person’s mind or personality characteristics at the time of writing. This paper provides a personality prediction system of different characteristics determining the personality of a person based on offline handwritten signature Images. Experiments are carried out using supervised learning techniques. Results shows a significant recognition rate and validates the effectiveness against the state-of-art techniques in comparison to similar works.
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