Neutralizing lighting non-homogeneity and background size in PCNN image signature for Arabic Sign Language recognition
Many feature generation methods have been developed using pulse-coupled neural network. Most of these methods succeeded to achieve the invariance against object translation, rotation and scaling but could not neutralize the bright background effect and non-uniform light on the quality of the generated features. To overcome the shortcomings, the paper proposes a new method to enhance the features quality. The Continuity Factor is defined and considered as a weight factor of the current pulse in signature generation process. This factor measures the simultaneous firing strength for connected pixels. The proposed new method is applied and compared to the previous methods. Through Arabic Sign Language recognition experiments, the superiority of the new method is shown.
pulse-coupled neural network (pcnn) continuity response (cr) continuity factor (cf) arabic sign language (asl)