Date of Publication :7th March 2016

Abstract: The proposed work describes the design and implementation of the hand gesture recognizer system for controlling the hardware appliance in real time. FPGA based implementation proposed for hand tracking system includes the image preprocessing state and feature extraction state that consists of bounding box and Center-Of-Mass based computation in terms of area segmentation. Through the features extraction state, the object’s Center-Of-Mass and bounding box attributes are extracted to be applied for gesture sign classification. The main modules in this image processing system employ the developed system exploits the parallelism architecture of the FPGA to achieve real time processing. There are many applications using hand gesture as a nature control interface, such as human machine interaction and interactive entertainment. With the advancement of computer vision and machine learning, the development of vision-based hand gesture recognition systems has received more and more attention in recent years. However, much previous research was focused on software algorithms running on a PC-based platform, which makes it inapplicable to real-time applications. In this proposed work we have implemented gesture recognition system based on improved optical flow was proposed to accelerate the execution and achieve real-time operation. Experimental results showed that the proposed framework is feasible and can reach the speed of 30 frames per second.

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