Hand Gesture Recognition Using OpenCV
Mrs. P. Rohini, Abishek Leo Kingston. J, Shriram.G.S, Siva Sankaran.S, Vasuki. G · Zenodo (CERN European Organization for Nuclear Research) · 2021
In human-computer interaction or sign language interpretation, recognizing hand gestures and detecting fingertips become ubiquitous in computer vision research. Hand gesture recognition provides an intelligent and natural way of human computer interaction. Its applications range from medical rehabilitation to consumer electronics control. In order to distinguish hand gestures, various kinds of sensing techniques are utilized to obtain signals for pattern recognition. This system can be divided into three parts according: Hand detection, hand gesture recognition, Edge detection for images, Integrating media. The system has two major advantages. First, it is highly modularized, and each of these steps is capsuled from others; second, the edge/contour detection of hand as well as gesture recognition is an add-on layer, which can be easily transplanted to other applications. The techniques used for image processing are hand gesture detection, edge detection, thresholding, contour detection. Using OpenCV, which provides a library collection of functions for different image processing techniques, these input images can be processed and corresponding key strokes will be generated.