Analysis on Handwritten Document Text to Identify Human Personality Characteristics by Using Preprocessing and Feature Extraction

  • Lukie Perdanasari Politeknik Elektronika Negeri Surabaya
  • Riyanto Sigit Politeknik Elektronika Negeri Surabaya
  • Achmad Basuki Politeknik Elektronika Negeri Surabaya
Keywords: Personal characters, Handwriting, Identification, Text document, Graphology


It is important that a company uses the right means to recruit employees with certain personal characteristics as needed. Nowadays, the techniques to respond to psychological tests on people’s characteristics have been widely understood by most job applicants, so that it is difficult to know their true personality. Graphology is a way to identify a person’s characteristics by analyzing the handwriting from the document text made by the applicant. The two types of text document of each applicant are obtained from people of different ages and different writing times. The methods of graphology used in this research for identifying the handwriting are preprocessing and feature extraction. The preprocessing method uses projection integrals, shear transformations, and template matching. While the feature extraction process applies 10 features, they are, margins, line spacing, space between words, size of writing, style, zone, direction of writing, slope of writing, width of writing and shape of the letter. The result of the experiment from five writers shows the accuracy of writing identification equals to 82%, while personality identification equals to 67,4%.


Download data is not yet available.

Author Biographies

Lukie Perdanasari, Politeknik Elektronika Negeri Surabaya
Postgraduate Student at Politeknik Elektronika Negeri Surabaya. Departement of Information and Computer Engineering
Riyanto Sigit, Politeknik Elektronika Negeri Surabaya
Lecturer at Politeknik Elektronika Negeri Surabaya. Departement of Information and Computer Engineering
Achmad Basuki, Politeknik Elektronika Negeri Surabaya
Lecturer at Politeknik Elektronika Negeri Surabaya. Departement of Information and Computer Engineering


Septa Dwikardana, Partical Handbook of Graphology, PT Kanisius(Yogyakarta), Ed.1, pp.18-15, 2014.

Dwi Sunar Prasetyono, Bedah Lengkap Grafologi Membaca Kepribadian Orang Lewat Tulisan Tangannya, DIVA Press (Yogyakarta),Ed.1, pp.79-175, 2012

Ricard Coll, Alicia Fornes, and Josep Llados, Graphological Analysis of Handwritten Text Documents for Human Resources Recruitment, IEEE International Conference on Document Analysis and Recognition, DOI 10.1109/ICDAR.2009.213, No.10, pp.1081-1085, 2009.

Somayeh Hashemi, Behrouz Vaseghi, and Fatemeh Torgheh, Graphology for Farsi Handwriting Using Image Processing Techniques, IOSR Journal of and Communication (IOSR-JECE), Vol.10, pp.01-07, No. 1, pp.01-07, 2015.

Champa H N, and K R Ananda Kumar, Automated Human Behavior Prediction through Handwriting Analysis, IEEE International Conference on Integrated Intelligent Computing, DOI 10.1109/ICIIC.2010.29, No.1, pp.161-165, 2010.

Parmeet Kaur Grewal, and Deepak Prashar, Behavior Prediction Through Handwriting Analysis. IJCST, Vol.3, No.2, pp.520-523, 2012

Behnam Fallah, and Hassan Khotanlou, Identify Human Personality Parameters Based On Handwriting Using Neural Network, International Conference on Artificial Intelligence and (IRANOPEN), 978-1-5090-2169-7/16, pp.120-126, 2016.

Nurul Ilmi, Tjokorda Agung Budi W, and Kurniawan Nur R, Handwriting Digit Recognition using Local Binary Pattern Variance and K-Nearest Neighbor Classification, International Conference on Information and Communication Technologies (ICoICT) ISBN: 978-1-4673-9879-4 (c) 2016 IEEE, 978-1-4673-9879-4, Vol.4, pp. 01-05, 2016.

Sri Widoretno, M Sarosa, and Muhammad Aziz Muslim, Implementasi Pengenalan Karakter Seseorang Berdasarkan Pola Tulisan Tangan, Jurnal EECCIS, Vol.7, No.2, pp.96-101, 2013.

Dewi Mutamimah, Pengenalan Kepribadian Orang Menggunakan Tulisan Tangan (Grafologi), D4 Final Project, EEPIS (Surabaya), 2015.

Kukuh Adi Prasetyo, Aplikasi Mobile Pengenalan Kepribadian Orang Menggunakan Grafologi, D4 Final Project, EEPIS (Surabaya), 2017.

Somaya Alma adeed, Colin Higgens, and Dave Elliman, Recognition of Off-Line Handwritten Arabic Words Using Hidden Markov Model Approach, IEEE, 1051-4651/02, pp.01-04, 2002.

Gaurav Jain, Jason Ko, Handwritten Digits Recognition, Project Report , University of Toronto, 2008.

Anita Ahmad Kasim, Retantyo Wardoyo and Agus Harjoko, Feature Extraction Methods for Batik Pattern Recognition: A Review, AIP Conference Proceedings Advances of Science and for Society, American, pp.070008-1 - 070008-8, 2016.

Nydia Amelinda Putri, Gelar Budiman, S.T., M.T. and Yuli Sun Hariyani, S.T.,M.T., Analisis Dan Implementasi Identifikasi Kepribadian Melalui Tulisan Tangan Pada Sistem Operasi Android Berdasarkan Pengolahan Citra, pp.1-8, 2016.

Leonid A. Mironovsky, Alexander V. Nikitin, Nina N. Reshetnikova and Nikolay V. Soloviev, Graphological Analysis and Identification of Handwritten Texts, Springer International Publishing, 978-3-319-67994-5_2, No.4, pp.11-36, 2018.

Ondˇrej Rohl´ık, Handwritten Text Analysis, Thesis, University Of West Bohemia In Pilsen, 2003.

Behnam Fallah and Hassan Khotanlou, Detecting features of human personality based on handwriting using learning algorithms, ACSIJ Advances in Science: an International Journal, Vol. 4, No.18, pp.31-37, 2015.

Listiana MP Dewi, Hadi Prayitno, Hendri Sopryadi, and Rachmansyah, Aplikasi Sistem Pakar Analisis Tulisan Tangan (Grafologi) Menggunakan Algoritma Fuzzy Logic Berbasis Android, Skripsi, STMIK GI MDP, 2012.

Eko Prasetyo, Pengolahan Citra Digital Dan Aplikasinya Menggunakan Matlab, Penerit ANDI (Yogyakarta), Ed.1, 2011.

Sofia Visa, Brian Ramsay, Anca Ralescu, and Esther van der Knaap, Confusion Matrix-basedature Selection, Science Department College of Wooster Wooster, 2011.

A. K. Santra and C. Josephine Christy, Genetic Algorithm and Confusion Matrix for Document Clustering, IJCSI International Journal of Science Issues, Vol. 9, No 2, pp.322-327, January 2012

Cinthia O.A. Freitas1, João M. de Carvalho2, José Josemar Oliveira Jr2, Simone B.K. Aires3, and Robert Sabourin, Confusion Matrix Disagreement for Multiple Classifiers, Pontificia Universidade Católica do Paraná, 2008.

Dirk B. Walther, Using Confusion Matrices to Estimate Mutual Information between Two Categorical Measurements, International Workshop on Pattern Recognition in Neuroimaging, DOI 10.1109/PRNI.2013.63, No.3, pp.220-224, 2013.

How to Cite
Perdanasari, L., Sigit, R., & Basuki, A. (2018). Analysis on Handwritten Document Text to Identify Human Personality Characteristics by Using Preprocessing and Feature Extraction. EMITTER International Journal of Engineering Technology, 6(2), 254-274.