Forecasting Personality Based On Calligraphy Using CNN and MLP

Authors

  • Nijil Raj N Dept. of Computer Science and Engineering, Younus College of Engineering and Technology, Kollam, Kerala, India
  • Mohammed Thaha Dept. of Computer Science and Engineering, Younus College of Engineering and Technology, Kollam, Kerala, India
  • Sushlin Grace Shaji Dept. of Computer Science and Engineering, Younus College of Engineering and Technology, Kollam, Kerala, India
  • Shibina S Dept. of Computer Science and Engineering, Younus College of Engineering and Technology, Kollam, Kerala, India

DOI:

https://doi.org/10.26438/ijcse/v8i7.4148

Keywords:

Graphology, Personality Traits, Calligraphy, Feature Extraction, CNN, MLP

Abstract

The way of living has modified since the digital age. Everything can be dealt with a tip of the finger, but all these luxuries are at risk at a cost of protection or fraud. Handwritten script or calligraphy explore about a person's personality. It tells concerning the character of the person and predicts the attribute like optimistic, Social Maturity, balanced, shy within the calligraphy as writing is linked with brain and it subconsciously leaves a sample. Various forms of calligraphy styles taken into thought are slope, baseline, top margin, word size, line spacing, word spacing, left or right or normal slant or irregular of the sentence, etc. The complete system evaluates the script based on the above-mentioned calligraphy styles and it is divided into three modules with the primary module being input the image of written text, then apply the preprocess to removes noise and sharpens the contrast of the image for better results. Extract the 7 features from each image in the dataset, then apply Convolutional Neural Network (CNN) combined with Multi Layer Perceptron(MLP). The proposed system reveals a better result compared to literature survey.

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Published

2020-07-31
CITATION
DOI: 10.26438/ijcse/v8i7.4148
Published: 2020-07-31

How to Cite

[1]
N. R. N, M. Thaha, S. G. Shaji, and S. S, “Forecasting Personality Based On Calligraphy Using CNN and MLP”, Int. J. Comp. Sci. Eng., vol. 8, no. 7, pp. 41–48, Jul. 2020.

Issue

Vol. 8 No. 7 (2020): IJCSE July Edition

Section

Research Article

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