E-Graphologist for Personality Profile
Deep learning of a person’s signature can reveal
his personality profile like fear, honesty, emotional state, thinking
style and much more. Analyzing signature can help in predicting
social skills, thinking style, work habits, achievements, etc. of the
writer. Type and style of signature can be judged by graphologist
based on curved start, single line, dot on letter, etc. Similarly
pattern recognition and image processing are used to analyze
signature and handwriting in our system. Here the signature is
considered as image and then prediction is performed through
different stages such as gray level conversion, calculating
threshold value, binary conversion etc. The most preferred
technique by researchers for personality prediction is 'Artificial
Signature for the Prediction of Personality Traits ”, 2017 1st
International Conference on Intelligent Systems and
Information Management (ICISIM),5-6 Oct. 2017 IEEE.
 Esmeralda Contessa Djamal, Risna Darmawati, Sheldy
Nur Ramdlan, “Application Image Processing to Predict
Personality Based on Structure of Handwriting and
Signature”. International Conference on Computer, Control,
Informatics and Its Applications 2013.
 Champa H N, K R AnandaKumar, “Automated Human
Behavior Prediction through Handwriting Analysis” First
International Conference on Integrated Intelligent Computing
2010. Anupam Varshney, Shalini Puri, “A Survey on human
personality identification on the basis of Handwriting using
ANN” , International Conference on Inventive Systems and
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Through Handwriting Using BPN ” , International Journal of
Advanced Research in Electronics and Communication
Engineering (IJARECE) Volume 6, Issue 2, February 2017.
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“Handwriting Analysis based on Segmentation Method for
prediction of Human Personality using Support Vector
Machine” , International Journal of Computer Applications
(0975 – 8887) Volume 8– No.12, October 2010
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Network for Human Behavior Prediction through Handwriting
Analysis.” , International Journal of Computer Applications
(0975 – 8887) Volume 2 – No.2, May 2010.
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"Recognition of Handwriting Based on Signature and Digit of
Character Using Multiple of Artificial Neural Networks in
Personality Identification ", Information Systems International
Conference (ISICO), 2 – 4 December 2013.
 Marcos Faundez-Zanuy, "Signature Recognition State-ofthe-
Art ", IEEE A&.B SYSTEMS MAGAZINE. JUI.Y. 2005.
 Prachi Joshi, Aayush Agarwal, Ajinkya Dhavale, Rajani
Suryavanshi, Shreya Kodolikar, “Handwriting Analysis for
Detection of Personality Traits using Machine Learning
Approach”, International Journal of Computer Applications
(0975 – 8887) Volume 130 – No.15, November2015.
 Prof. Seema Kedar, Ms. Vaishnavi Nair, Ms. Shweta
Kulkarni ” Personality Identification through Handwriting
Analysis: A Review ”, International Journal of Advanced
Research in Computer Science and Software Engineering ,
Volume 5, Issue 1, January 2015.
 Parmeet Kaur Grewal, Deepak Prashar, “Behavior
Prediction Through Handwriting Analysis”, International
Journal of Computer Science and technology, June 2012.
 G.Sheikholeslami, S.N.Srihari, V.Govindaraju,
“COMPUTER AIDED GRAPHOLOGY”, 28 February 2013,
 Ujjwal Bhattacharya, and B.B. Chaudhuri, “Handwritten
Numeral Databases of Indian Scripts and Multistage
Recognition of Mixed Numerals”, IEEE TRANSACTIONS
ON PATTERN ANALYSIS AND MACHINE
INTELLIGENCE, VOL. 31, NO. 3, MARCH 2009.
 Esmeralda C. Djamal, Febriyanti, “Identification of
Speed and Unique Letter of Handwriting Using Wavelet and
Neural Networks ”, Proceeding of International Conference
on Electrical Engineering, Computer Science and Informatics
(EECSI 2015), Palembang, Indonesia, 19 -20 August 2015.
 Ankur M. Bobade, Prof. N. N. Khalsa, Dr. S. M.
Deshmukh, “Prediction of Human Character through
Automated Script Analysis”, International Journal of Scientific
& Engineering Research, Volume 5, Issue 10, October-2014.
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