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Analysis of signature for the prediction of personality traits

机译:预测人格特质的签名分析

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摘要

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.
机译:签名可以提供有关人的不同情绪状态和思维方式的最丰富信息。签名分析是预测人格的最有效,最可靠的指标之一。它揭示了真实的人格,包括恐惧,诚实和许多其他个人人格特质。这可以借助一些功能来实现,例如签名下的下划线,字母上出现圆点,弯曲的起始点,结束的笔划以及断开的条纹。本文着重于上述功能。该数据库有10个签名的60个签名,每个签名有6个样本,并且已在500dpi分辨率的扫描仪上正确扫描。通过将签名分为五个类别(左,右,上,中和下)来评估性能。人工神经网络和结构识别算法用于人格预测,准确率分别为100%,95%,94%,96%和92%。研究的意义在于揭示犯罪学,医学上的人格特质。和咨询。

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