An Efficient Approach for the Recognition of Hand Gestures from Very Low Resolution Images

In this paper, a simple and effective approach for the recognition of hand gestures from very low resolution images is proposed. Enhancement of the low resolution images has always been the key focus in the processing of the digital images. Images with resolution as low as [50×50 pixels] are also considered for recognition. The gestures under consideration here are the number of fingers (one, two, three, four or five) raised by the person. The low resolution gesture image captured from web camera, mobile phone, or low cost cameras is processed systematically to output the number of fingers raised. Simple concepts of the geometry of the hand have been used for the recognition of hand gesture from the input low resolution images. The proposed method extracts the hand gesture directly from the low resolution image without the need of reconstruction to a high resolution image or use of any classifier. The proposed method is based on the generation of a mask for the image which is critical in the recognition of the hand gesture. This method is tested on publically available dataset of Marcel-Triesch. The high accuracy of the experimental results show the superior performance of the proposed method for the recognition of hand gesture from low resolution images.