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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References
Lokhande, V.R., Gawali, B.W.: Analysis of signature for the prediction of personality traits. In: 2017 1st International Conference on Intelligent Systems and Information Management (ICISIM), 5–6 October 2017. IEEE (2017)
Djamal, E.C., Darmawati, R., Ramdlan, S.N.: Application image processing to predict personality based on structure of handwriting and signature. In: International Conference on Computer, Control, Informatics and Its Applications (2013)
Champa, H.N., AnandaKumar, K.R.: Automated human behavior prediction through handwriting analysis. In: First International Conference on Integrated Intelligent Computing (2010)
Varshney, A., Puri, S.: A survey on human personality identification on the basis of handwriting using ANN. In: International Conference on Inventive Systems and Control (ICISC-2017) (2017)
Sharma, V., Depti, Er.: Human behavior prediction through handwriting using BPN. Int. J. Adv. Res. Electron. Commun. Eng. (IJARECE) 6(2), 57–62 (2017)
Prasad, S., Singh, V.K., Sapre, A.: Handwriting analysis based on segmentation method for prediction of human personality using support vector machine. Int. J. Comput. Appl. 8(12), 25–29 (2010). (0975 – 8887)
Champa, H.N., AnandaKumar, K.R.: Artificial neural network for human behavior prediction through handwriting analysis. Int. J. Comput. Appl. 2(2), 36–41 (2010). (0975 – 8887)
Djamal, E.C., Ramdlan, S.N., Saputra, J.: Recognition of handwriting based on signature and digit of character using multiple of artificial neural networks in personality identification. In: Information Systems International Conference (ISICO), 2–4 December 2013
Faundez-Zanuy, M.: Signature recognition state-of-the-art. IEEE Aerosp. Electron. Syst. Mag. 20(7), 28–32 (2005)
Joshi, P., Agarwal, A., Dhavale, A., Suryavanshi, R., Kodolikar, S.: Handwriting analysis for detection of personality traits using machine learning approach. Int. J. Comput. Appl. 130(15), 40–45 (2015). (0975 – 8887)
Kedar, S., Nair, V., Kulkarni, S.: Personality identification through handwriting analysis: a review. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 5(1), 548–556 (2015)
Grewal, P.K., Prashar, D.: Behavior prediction through handwriting analysis. Int. J. Comput. Sci. Technol. 3(2), 520–523 (2012)
Sheikholeslami, G., Srihari, S.N., Govindaraju, V.: Computer aided graphology. Research Gate, 28 February 2013
Bhattacharya, U., Chaudhuri, B.B.: Handwritten numeral databases of Indian Scripts and multistage recognition of mixed numerals. IEEE Trans. Pattern Anal. Mach. Intell. 31(3), 444–457 (2009)
Djamal, E.C., Febriyanti: Identification of speed and unique letter of handwriting using wavelet and neural networks. In: Proceeding of International Conference on Electrical Engineering, Computer Science and Informatics (EECSI 2015), Palembang, Indonesia, 19–20 August 2015
Bobade, A.M., Khalsa, N.N., Deshmukh, S.M.: Prediction of human character through automated script analysis. Int. J. Sci. Eng. Res. 5(10), 1157–1161 (2014)
https://www.futurepointindia.com/article/en/your-nature-is-revealed-in-your-signature-8792
Bala, A., Sahaa, R.: An improved method for handwritten document analysis using segmentation, baseline recognition and writing pressure detection. In: 6th International Conference on Advances in Computing & Communications, ICACC 2016, Cochin, India, 6–8 September 2016
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Shete, P.S., Thengade, A. (2020). Personality Trait with E-Graphologist. In: Smys, S., Tavares, J., Balas, V., Iliyasu, A. (eds) Computational Vision and Bio-Inspired Computing. ICCVBIC 2019. Advances in Intelligent Systems and Computing, vol 1108. Springer, Cham. https://doi.org/10.1007/978-3-030-37218-7_14
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DOI: https://doi.org/10.1007/978-3-030-37218-7_14
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