Smart hand gestures recognition using K-NN based algorithm for video annotation purposes

<span>Sign languages are the most basic and natural form of which were used even before evolution spoken languages. These sign developed using various "gestures" that made hand palm. Such gestures called "hand gestures". Hand being widely as an international assistive communication method for deaf people many life aspects such sports, traffic control religious acts. However, meanings vary among different civilization cultures. Therefore, because importance understanding gestures, this study presents a procedure whichcan translate into annotated explanation. The proposed system implements image video processing recently conceived one important technologies. initially, analyzes classroom input, then extracts vocabulary twenty gestures. Various methods have been applied sequentially, namely: motion detection, RGB to HSV conversion, noise removing labeling algorithms. extraction parameters is determined by K-NN algorithm eventually determine gesture and, hence showing their meanings. To estimate performance method, experiment database performed. results showed suggested has average recognition rate 97%. </span>