Hand Gestures Detecting Using Radon And Fan Beam Projection Features
Recognizing hand gestures is one of the most efficient ways of human interaction with a computer and an important field in computer vision and machine learning. This subject matter enables many applications to allow users to communicate the interfaces of different systems, without the need for additional hardware. Therefore, the primary goal of gesture recognition is to create systems in order to identify specific human gestures and use them to transmit information and signals or control various devices. There are more research in the field of pattern recognition especially in gesture recognition .Some of these research focus on dimension reduction , other on recognition model, and in features selection type..etc. In this research, the static hand gesture is detected depending on applying radon features and fan beam projection on hand images to compute the projection by given angles. The reason for adopting these techniques is to take its advantages in giving features not related to the shape and size of the object . The decision tree model is used in recognition stage to detect five different hand gestures, and all the results are reported.
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