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International Conference on Computer Vision and Image Processing

CVIP 2019: Computer Vision and Image Processing pp 25–35Cite as

Profession Identification Using Handwritten Text Images

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1148))

Abstract

A writer handwriting depicts various information and it gives the insights into the physical, mental and emotional state of the writer. This art of analyzing and studying handwriting is graphology. The prime features of handwriting such as margins, slanted, the baseline can tell the characteristics of a writer. The writer handwriting analysis reveals strokes and patterns through which identification and understanding the personality of a writer is possible. The writing of a person molds into various shapes and styles, starting from school until the struggle for his/her career. If we examine the writings of a person from different stages of his/her life then we will see that there are many differences in the shapes, styles, and sizes of the characters. The proposed work analyze the handwriting data written by the writer’s from different professions and classify them based on the top features that characterize their profession. In this paper, the profession of a writer is identified by analyzing the features of writer’s offline handwritten images. The previous work mostly includes determining various traits like honesty, emotional stability of a writer. The Proposed work uses the CNN based model for the feature extraction from the writer’s offline handwritten images.

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Author information

Authors and Affiliations

  1. Indian Institute of Technology, Roorkee, Roorkee, India

    Parveen Kumar & Ambalika Sharma

  2. National Institute of Technology Uttarakhand, Srinagar, Garhwal, India

    Parveen Kumar, Manu Gupta & Mayank Gupta

Authors
  1. Parveen Kumar
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  2. Manu Gupta
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  3. Mayank Gupta
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  4. Ambalika Sharma
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Corresponding author

Correspondence to Parveen Kumar .

Editor information

Editors and Affiliations

  1. Malaviya National Institute of Technology, Jaipur, Rajasthan, India

    Neeta Nain

  2. Malaviya National Institute of Technology, Jaipur, Rajasthan, India

    Santosh Kumar Vipparthi

  3. Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Balasubramanian Raman

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Cite this paper

Kumar, P., Gupta, M., Gupta, M., Sharma, A. (2020). Profession Identification Using Handwritten Text Images. In: Nain, N., Vipparthi, S., Raman, B. (eds) Computer Vision and Image Processing. CVIP 2019. Communications in Computer and Information Science, vol 1148. Springer, Singapore. https://doi.org/10.1007/978-981-15-4018-9_3

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  • DOI: https://doi.org/10.1007/978-981-15-4018-9_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-4017-2

  • Online ISBN: 978-981-15-4018-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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