Since the dynamic gesture recognition algorithm is influenced by rotation

translation and scaling

and real-time gesture recognition is still a challenging issue

we propose a dynamic gesture recognition algorithm which is based on the combination of gesture binary descriptor and Hausdorff-like distance template matching.Firstly

we converted the segmented gesture image to the standardized image

then calculated the main direction of gesture in the image

and built a 2D rectangular coordinate system to extract the gesture features.Secondly

the specific dynamic gesture type can be identified according to changes in the amount of gesture pixel points from the top five frames.Next

we used gesture binary descriptor to select a part of gesture from the specific dynamic gesture type.Finally

the method of Hausdorff-like distance template matching is used to recognize the final gesture.The main innovation of this paper embodies in two aspects.Firstly

the dynamic gesture type recognition and the method of gestures binary descriptor matching proposed in this paper greatly shorten the time cost of dynamic gesture recognition.Secondly

Hausdorff-like distance method with the main direction of gesture not only has the in-variance on rotation

translation and scaling gestures

but also has a higher recognition rate on smaller gestures.Experimental results show that this algorithm can achieve real-time correct recognition of gestures in relatively stable light conditions.The overall recognition rate can reach 95%

the recognition rate of scal-ing gestures is more than 92% and the recognition rate of rotation gestures is more than 87%.This algorithm has been applied in a human-computer interface system based on hand gesture.