Association of Job and Demographical Risk Factor with Occurrence of Neck Pain Among Hand Screen Printing Workers

Shankar, S.; Kumar, R. Naveen; MohanKumar, P.S.; Karthick, J.; Pradeep, S.

doi:10.1007/978-981-10-4980-4_17

Cited by 6 publications

(1 citation statement)

References 10 publications

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“…Neither the flows OCR, ICR and IWR accessible available can be connected to take care of the issue of content acknowledgment in old archives. In the event that this circumstance appears to be practically evident on account of original copies, as a result of their inclination, it ought to be less justifiable for the printed books [9]. Rather, notwithstanding for this sort of curio, specifically for books created by handprinting, the circumstance is fundamentally the same as that of the compositions.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Feature Extraction and Multiclass SVM Based Ancient Character Recognition

Balasubrmanie*¹,

Vellingiriraj²

2019

IJRTE

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Ancient character recognition is the most difficult task due to their different formats and less frequent knowledge about the ancient characters. This is performed in the previous research work namely Shape and Size aware Character Recognition and Conversion System (SSCR-CS). This research work proved better character recognition outcome. However this research work might be reduced in performance with lesser detailed information in the images. This is resolved in the proposed research work by introducing the most recent techniques for the character recognition outcome. This is attained by introducing the method namely Hybrid Feature Extraction and Multiclass SVM based recognition method (HFE-MCSVM). In this research work, initially image preprocessing is performed by using Gabor filter. After preprocessing segmentation of characters is performed by using overlapped character segmentation method. After segmentation character recognition is done by introducing the method namely hybrid feature extraction with Multiclass SVM classification approach. The overall assessment of the research work is done in the matlab simulation environment and then it is proved the proposed HFE-MCSVM shows better performance.

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Section: Introductionmentioning

confidence: 99%