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Experimental Face Recognition Using Applied Deep Learning Approaches to Find Missing Persons Read chapter Read first chapter

2023 | OriginalPaper | Chapter

Convexity Defects-Based Fingertip Detection and Hand Gesture Recognition

Authors : Soumi Paul, Shrouti Gangopadhyay, Ayatullah Faruk Mollah, Subhadip Basu, Mita Nasipuri

Published in: Proceedings of International Conference on Frontiers in Computing and Systems

Publisher: Springer Nature Singapore

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Abstract

Vision-based hand gesture recognition is perhaps the most widely used technique for human–computer interaction technology with special application toward sign languages used by differently abled people. Perhaps the most important step in such a gesture recognition system is feature extraction. In this paper, we use a novel fingertip detection mechanism based on convexity defects and use nine geometrical features that are translation and rotation invariant. We use seven different classifiers on two different public hand digit datasets (NTU hand digit dataset and SP-EMD color-depth hand gesture dataset) and find that for both the datasets, the random forest classifier gives the best classification accuracy (94.2% and 90.1%, respectively).

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Metadata
Title
Convexity Defects-Based Fingertip Detection and Hand Gesture Recognition
Authors
Soumi Paul
Shrouti Gangopadhyay
Ayatullah Faruk Mollah
Subhadip Basu
Mita Nasipuri
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Proceedings of International Conference on Frontiers in Computing and Systems

Print ISBN: 978-981-19-0104-1

Electronic ISBN: 978-981-19-0105-8

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-19-0105-8_21