Analysis of signature for the prediction of personality traits

2017 1st International Conference on Intelligent Systems and Information Management (ICISIM) Pub Date : 2017-10-01 DOI:10.1109/ICISIM.2017.8122145

Vaishali R. Lokhande, B. Gawali

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引用次数: 17

Abstract

The richest information about different emotional states and thinking styles of the person is carried by signature The signature analysis is one of the most effective and reliable indicator for prediction of personality. As it reveals the true personality which includes fears, honesty and many other individual personality traits. This can happen with the help of few features like underscores below signature, appearance of dot on the letter, curved start, ending stroke, and streaks disconnected. This paper is focused on above mentioned features. The database has 60 signatures of 10 different persons with 6 samples of each and is properly scanned at 500dpi resolution scanner. The performance is evaluated by splitting a signature into five categories-left, right, upper, middle and bottom. An artificial neural network and structural identification algorithm is used for the prediction of personality and the obtained accuracy rate is 100%, 95%, 94%, 96% and 92% respectively The significance of work is to reveal personality traits in criminology, medical science and counseling.

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个性特征预测的签名分析

一个人的不同情绪状态和思维方式最丰富的信息是由签名承载的，签名分析是预测性格最有效、最可靠的指标之一。因为它揭示了真实的个性，包括恐惧、诚实和许多其他的个性特征。这可以通过一些特征来实现，比如签名下面的下划线、字母上的圆点、弯曲的起始、结束笔画和断开的条纹。本文主要针对上述特点进行研究。该数据库有10个不同人的60个签名，每个签名有6个样本，并在500dpi分辨率扫描仪上正确扫描。性能是通过将签名分为五类来评估的——左、右、上、中、下。采用人工神经网络和结构识别算法进行人格预测，获得的准确率分别为100%、95%、94%、96%和92%，工作意义在于揭示犯罪学、医学和心理咨询领域的人格特征。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2017 1st International Conference on Intelligent Systems and Information Management (ICISIM)

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