Graphology Analysis for Handwritten Latin and Arabic

Pengarang

  • Shafinaz Mohammad Niyaz Khan Department of Information Technology and Multimedia, Faculty of Science and Information Technology, International Islamic University College Selangor, Selangor, Malaysia
  • Juzlinda Mohd Ghazali Department of Computer Science, Faculty of Science and Information Technology, International Islamic University College Selangor, Selangor, Malaysia

DOI:

https://doi.org/10.53840/myjict4-2-87

Kata kunci:

Graphology, Personality traits, Latin scripts, Farsi scripts, Arabic scripts

Abstrak

Graphology is a scientific method of analyzing, identifying, evaluating and understanding personality through strokes and patterns revealed by handwriting. Personality that can be revealed through handwriting includes emotional outlay, fear, honesty, defense and many other individual personality traits. Graphology analysis is normally been used by teachers, lecturers, business people, company owners, police, forensic investigators, forensic psychologist, parents, spouse and many others. Numerous researches had been done on Latin handwritten script. Among the variants in Arabic handwritten script that are mostly been researched and receive considerable attention in recent years are Farsi (Persian) and Urdu. However, not much highlight had been given to Arabic script. This paper highlights the current research on graphology and the purpose of researching graphology towards Arabic handwritten scripts.

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Rujukan

Champa, H. N., & AnandaKumar, K. R. (2010). Artificial Neural Network For Human Behavior Prediction Through Handwriting Analysis. International Journal of Computer Applications. 2(2), 36- 41.

Champa, H. N., & AnandaKumar, K. R. (2011). Rule-Based Approach for Personality Prediction Through Handwriting Analysis. International Journal of Computational Intelligence and Healthcare Informatics. 4(1), 27-29.

Crepieux-Jamin, J. (1951). L´ecriture et le caractere (The Writing and the Character). Presses Univ. de France. 14th edition.

Fallah, B., & Khotanlou, H. (2015). Detecting Features of Human Personality Based on Handwriting Using Learning Algorithms. Advances in Computer Science: an International Journal. 4(6), 31-37.

Hashemi, S., Vaseghi, B., & Torgheh, F. (2015). Graphology for Farsi Handwriting Using Image Processing Techniques. IOSR J. Electron. Commun. Eng.(IOSR-JECE). 10(3), 01-07.

Ibarguren, U. (2016). Handwriting & Graphology 2016. Retrieved 15 August, 2019, from http://www.handwriting-graphology.com

Karami, A. (2017). Study on Connections Between Signature and Personality Using Eysenck Test: A Case Study of Iranian Signatures. American Journal of Applied Psychology. 6(1), 6-14.

Oliveira, L. S., Justino, E., Freitas, C., & Sabourin, R. (2005, June). The Graphology Applied to Signature Verification. In 12th Conference of the International Graphonomics Society. 286-290.

Pratiwi, D., Santoso, G. B., & Saputri, F. H. (2016). Personality Type Assessment System by Using Enneagram-Graphology Techniques on Digital Handwriting. International Journal of Computer Applications. 147(11).

Toraichi, K., Horiuchi, T., & Haruki, R. (1995, August). Observation Method for Mathematical Graphology. In Proceedings of 3rd International Conference on Document Analysis and Recognition. 2, 656-659. IEEE.

Wijaya, W., Tolle, H., & Utaminingrum, F. (2018). Personality Analysis Through Handwriting Detection Using Android Based Mobile Device. Journal of Information Technology and Computer Science. 2(2).

Yaacob, M., A. N., Zainab, Mahmud, R., & Che Nasir, N. E. (2001, September). Digitisation of an Endangered Written Language: The Case of Jawi Script. In The International Symposium on Languages in Cyberspace. 26-27.

Diterbitkan

2019-12-31

Terbitan

Bahagian

Articles

Cara Memetik

Mohammad Niyaz Khan, S., & Mohd Ghazali, J. (2019). Graphology Analysis for Handwritten Latin and Arabic. Malaysian Journal of Information and Communication Technology (MyJICT), 4(2), 99-107. https://doi.org/10.53840/myjict4-2-87

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