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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/16768
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dc.contributor.authorKumar P.-
dc.contributor.authorGupta M.-
dc.contributor.authorGupta M.-
dc.contributor.authorSharma, Ambalika-
dc.contributor.editorNain N.-
dc.contributor.editorVipparthi S.K.-
dc.contributor.editorRaman B.-
dc.date.accessioned2020-12-02T14:28:25Z-
dc.date.available2020-12-02T14:28:25Z-
dc.date.issued2020-
dc.identifier.citationProceedings of Communications in Computer and Information Science, (2020), 25- 35-
dc.identifier.isbn9.78981E+12-
dc.identifier.issn18650929-
dc.identifier.urihttps://doi.org/10.1007/978-981-15-4018-9_3-
dc.identifier.urihttp://repository.iitr.ac.in/handle/123456789/16768-
dc.description.abstractA 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. © Springer Nature Singapore Pte Ltd 2020.-
dc.language.isoen_US-
dc.publisherSpringer-
dc.relation.ispartofProceedings of Communications in Computer and Information Science-
dc.subjectFeature extraction-
dc.subjectHandwritten document-
dc.subjectPersonality prediction-
dc.titleProfession identification using handwritten text images-
dc.typeConference Paper-
dc.scopusid57214054754-
dc.scopusid55465749900-
dc.scopusid57213189329-
dc.scopusid55482822100-
dc.affiliationKumar, P., Indian Institute of Technology, Roorkee, Roorkee, India, National Institute of Technology Uttarakhand, Garhwal, Srinagar, India-
dc.affiliationGupta, M., National Institute of Technology Uttarakhand, Garhwal, Srinagar, India-
dc.affiliationGupta, M., National Institute of Technology Uttarakhand, Garhwal, Srinagar, India-
dc.affiliationSharma, A., Indian Institute of Technology, Roorkee, Roorkee, India-
dc.description.correspondingauthorKumar, P.; National Institute of Technology Uttarakhand, Garhwal, India; email: parveen.cse@nituk.ac.in-
dc.identifier.conferencedetails4th International Conference on Computer Vision and Image Processing, CVIP 2019, 27-29 September 2019-
Appears in Collections:Conference Publications [EE]

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