Syeda Asra

Work place: Appa Institute of Engineering & Technology,Visvesvaraya Technological University Belguam, Brahmpur, Gulbarga 585102, India.

E-mail: asrascholar@gmail.com

Website:

Research Interests: Computational Science and Engineering, Computational Engineering, Computer systems and computational processes, Theoretical Computer Science

Biography

Syeda Asra (born July 11, 1977) is an Indian researcher, keen in understanding the unique features within oneself and currently working as an Associate Professor in the department of Computer Science & Engineering in Appa Institute of Engineering & Technology, Kalaburagi, India

Author Articles
Personality Trait Identification Using Unconstrained Cursive and Mood Invariant Handwritten Text

By Syeda Asra Shubhangi D.C

DOI: https://doi.org/10.5815/ijeme.2015.05.03, Pub. Date: 8 Oct. 2015

Identification of Personality is a complex process. Personality traits are stable over time .Individual's behavior naturally varies from occasion to occasion. But there is a core consistency which defines the true nature. The paper addresses this issue of behavior. Graphology is normally a technique used to identify the traits. Accuracy of this technique depends on how skilled the analyst is. Although human intervention in handwriting analysis has been effective, but it is costly and prone to fatigue. An automation of handwritten text is proposed. Basically we have considered three important features in the direction of orientation of the lines :(i) up hill (ii) down hill (iii) constant line. Edge histogram and bounding boxes was used for feature extraction .Known classifiers like SVM & ANN are used for training and the results were compared. The results were about 98% for SVM & 70% with ANN. The analysis was done using single line.

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