Personality Trait with E-Graphologist
25 Sep 2019-pp 120-130
TL;DR: The main objective here is predicting authors personality trait based on features such as Skewness, Pen Pressure, Aspect Ratio, Margin, and the difference between the first and last letter of the signature.
Abstract: Signature analysis helps in analyzing and understanding individual’s personality. Graphology is the scientific technique that helps us predict the writer’s personality. Different types of strokes and patterns in writer’s signature are considered for predicting their personality trait. Social skills, achievements, work habits, temperament, etc. can be predicted by using the writer’s signature. It helps us in understanding the person in a better way. As signature is directly related and develops a positive impact on your social life, personal life as well as for your career it is essential to practice correct signature for good results. The main objective here is predicting authors personality trait based on features such as Skewness, Pen Pressure, Aspect Ratio, Margin, and the difference between the first and last letter of the signature. As your signature has a direct impact on any of your assets and career, the proposed system will also provide suggestions for improvement in the signature if needed. This research paper proposes an off-line signature analysis. We have created our own dataset for the analysis purpose. We have also provided them with some questionnaire to check the accuracy of the proposed system.
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TL;DR: P pioneering development of two databases for handwritten numerals of two most popular Indian scripts, a multistage cascaded recognition scheme using wavelet based multiresolution representations and multilayer perceptron classifiers and application for the recognition of mixed handwritten numeral recognition of three Indian scripts Devanagari, Bangla and English.
Abstract: This article primarily concerns the problem of isolated handwritten numeral recognition of major Indian scripts. The principal contributions presented here are (a) pioneering development of two databases for handwritten numerals of two most popular Indian scripts, (b) a multistage cascaded recognition scheme using wavelet based multiresolution representations and multilayer perceptron classifiers and (c) application of (b) for the recognition of mixed handwritten numerals of three Indian scripts Devanagari, Bangla and English. The present databases include respectively 22,556 and 23,392 handwritten isolated numeral samples of Devanagari and Bangla collected from real-life situations and these can be made available free of cost to researchers of other academic Institutions. In the proposed scheme, a numeral is subjected to three multilayer perceptron classifiers corresponding to three coarse-to-fine resolution levels in a cascaded manner. If rejection occurred even at the highest resolution, another multilayer perceptron is used as the final attempt to recognize the input numeral by combining the outputs of three classifiers of the previous stages. This scheme has been extended to the situation when the script of a document is not known a priori or the numerals written on a document belong to different scripts. Handwritten numerals in mixed scripts are frequently found in Indian postal mails and table-form documents.
306 citations
TL;DR: An automatic method has been proposed to predict the psychological personality of the writer and it gives about 94% of accuracy rate with RBF kernel.
Abstract: Handwriting analysis is a method to predict personality of an author and to better understand the writer. Allograph and allograph combination analysis is a scientific method of writer identification and evaluating the behavior. To make this computerized we considered six main different types of features: (i) size of letters, (ii) slant of letters and words, (iii) baseline, (iv) pen pressure, (v) spacing between letters and (vi) spacing between words in a document to identify the personality of the writer. Segmentation is used to calculate the features from digital handwriting and is trained to SVM which outputs the behavior of the writer. For this experiment 100 different writers were used for different handwriting data samples. The proposed method gives about 94% of accuracy rate with RBF kernel. In this paper an automatic method has been proposed to predict the psychological personality of the writer. The system performance is measured under two different conditions with the same sample.
69 citations
TL;DR: A method has been proposed to predict the personality of a person from the baseline, the pen pressure and the letter„t‟ as found in an individual’s handwriting as inputs to the Artificial Neural Network which outputs the personality trait of the writer.
Abstract: Handwriting Analysis or Graphology is a scientific method of identifying, evaluating and understanding personality through the strokes and patterns revealed by handwriting. Handwriting reveals the true personality including emotional outlay, fears, honesty, defenses and many others. Professional handwriting examiners called graphologist often identify the writer with a piece of handwriting. Accuracy of handwriting analysis depends on how skilled the analyst is. Although human intervention in handwriting analysis has been effective, it is costly and prone to fatigue. Hence the proposed methodology focuses on developing a tool for behavioral analysis which can predict the personality traits automatically with the aid of a computer without the human intervention. In this paper a method has been proposed to predict the personality of a person from the baseline, the pen pressure and the letter„t‟ as found in an individual‘s handwriting. These parameters are the inputs to the Artificial Neural Network which outputs the personality trait of the writer. The performance is measured by examining multiple samples.
52 citations
TL;DR: Technological advances have made possible new perspectives for signature recognition, by means of capturing devices which provide more than the simple signature image: pressure, acceleration, etc., making it even more difficult to forge a signature.
Abstract: A summarization of one of the most successful behavioral biometric recognition methods: signature recognition. Probably this is one of the oldest biometric recognition methods, with high legal acceptance. Technological advances have made possible new perspectives for signature recognition, by means of capturing devices which provide more than the simple signature image: pressure, acceleration, etc., making it even more difficult to forge a signature.
51 citations
05 Aug 2010
TL;DR: In this paper, a method has been proposed to predict the personality of a person from the baseline, the pen pressure, the letter t, the lower loop of letter y and the slant of the writing as found in an individual's handwriting.
Abstract: Handwriting Analysis or Graphology is a scientific method of identifying, evaluating and understanding personality through the strokes and patterns revealed by handwriting. Handwriting reveals the true personality including emotional outlay, fears, honesty, defenses and many others. Professional handwriting examiners called graphologist often identify the writer with a piece of handwriting. Accuracy of handwriting analysis depends on how skilled the analyst is. Although human intervention in handwriting analysis has been effective, it is costly and prone to fatigue. Hence the proposed methodology focuses on developing a tool for behavioral analysis which can predict the personality traits automatically with the aid of a computer without the human intervention. In this paper a method has been proposed to predict the personality of a person from the baseline, the pen pressure, the letter‘t’, the lower loop of letter ‘y’ and the slant of the writing as found in an individual’s handwriting. These parameters are the inputs to a Rule-Base which outputs the personality trait of the writer.
47 citations