INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Hand gesture recognition is one technology that can figure out what a person is doing with their hands in a live video. The way the hand moves fits into a given field of study. In this study, creating a system that can recognize hand gestures is one of the hard tasks that combines two big problems. First, there is hand detection. Another challenge is making a sign that can be utilized with just one hand at a time. This study focuses on how a system might detect, recognize, and understand hand gestures by computer vision, even when the position, orientation, location, and size of the hands can change. In this system, several kinds of gestures, such numbers and sign languages, need to be made for this project to work successfully. Before the image processing is done, the picture from the real-time video is analyzed with a Haar-cascaded Classifier to find the hand gesture or, in other words, to find the appearance of a hand in a frame. In this project, the hand will be found by utilizing Python programming and the ideas of Region of Interest (ROI). The part of the findings that will be explained in detail will be the simulation, as the only difference between the simulation and the hardware implementation is the source code to read the real-time input video. Using the ideas of hand segmentation and the hand detection system that uses the Haar-cascade classifier, hand gesture recognition may be built using Python and OpenCV..
Keywords:
hand gesture, human computer interaction (HCI), contour, convex hull, convexity defects, gesture recognition, python, openCV.
Cite Article:
"Hand Gesture Recognition Techniques For Human Computer Interaction Using OpenCv", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.a127-a132, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305017.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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