Author : Adarsh Pathak 1
Date of Publication :17th May 2021
Abstract: This paper compares the performance of two methods for hand gesture recognition for number identification. The image is captured employing a web camera system and undergoes many process stages before recognition of the numbers. Some of these stages include capturing the images, noise elimination, application of the CNN, and contour algorithm to predict the number. Once the hand is been placed in the region of interest the CNN algorithm predicts the number and gives output in the frame using deep learning techniques, whereas the contour algorithm creates the boundary of the hand and predict the number using the convexity hull defects algorithm and gives the output in the frame. The proposed methods of CNN and Contour achieved the accuracy of 91.2% and 93.8% respectively.
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