Gesture Recognition Based on Hexagonal Structure Histograms of Oriented Gradients

Abstract

Feature extraction methods of image directly affect the feature recognition results based on computer vision-based gesture recognition. This paper proposed a gesture feature extraction method of hexagonal structure, which is based on histograms of oriented gradients. This paper transforms the quadrilateral structure into hexagonal structure of the image and defines hexagonal block structure. Using different structures, different sizes of hexagonal blocks extract gesture feature and recognize on different sizes image. Experimental results show that hexagonal structure block is more appropriate than conventional histograms of oriented gradients structure block, the hexagonal structure histograms of oriented gradients feature extraction method is more efficient than the square and circular structure histograms of oriented gradients feature, using gentle_adaboost classifier achieved higher recognition rate.