Hand Gesture Recognition Based on Fourier Descriptors with Complex Backgrounds
Chongqing Liu · Jisuanji fangzhen · 2005
Hand gesture is one of the most popular communication methods in everyday life.Hand gesture recognition research has gained a lot of attentions because of its applications for interactive human-machine interface and virtual environments. But currently, in the vision-based hand gesture recognition, almost all the technologies on hand gesture segmentation are based on simple background or on gloves in special colors. However, this paper presents a method that segments the hand gestures with complex backgrounds through the combination of motion and skin color based on KL Transformation,in contrast with traditional hand gesture segmentation based on RGB color model in some environments.After the pretreatment to hand gesture region, we use a normalized Fourier descriptor, which is more accurate than the traditional Fourier descriptor,to select the hand gesture features and use the traditional 3 levels BP network to perform hand gesture recognition.Finally, the average recognition rate is 95.9% on the training set and 95% on the testing set.