Real-Time Hand Gesture Recognition forEmbedded System

A system with low-cost hardware computer webcam as the replacement of mouse click is being applied in this research. In order to capture good image of hand in vision based system, various segmentation techniques proposed by other researchers are combined and tested to enhance the quality of segmentation image. Canny edges and Otsu threshold technique are used to segment the hand image while convex hull and convexity defects algorithm are used to extract the image of hand features. Embedded hardware (Arduino) board is employed for validating the signal sent using hand gesture to replace LEFT CLICK, RIGHT CLICK, MOVE cursors. An experiment is set up to determine the accuracy in percentage of this work with ten test subjects. They were prearranged for five minutes to become familiar with the hand tracking system after the initial attempt. The findings revealed that users are better trained in the second trial after five minutes training. The results significantly improved from 33.3 % to 52.6 % for LEFT CLICK, 46.7% to 61 % improvement for RIGHT CLICK while 56.7% to 77.3% for MOVE cursor.