PSO-based Optimized Canny Technique for Efficient Boundary Detection in Tamil Sign Language Digital Images

For the hearing impaired, sign language is the most prevailing means of communication for their day-to-day life. It is always a challenge to develop an optimized automated system to recognize and interpret the implication of signs expressed by the hearing impaired. There are a wide range of algorithms developed for SLR, in which only few considerable approaches are carried out in Tamil Sign Language Recognition. This paper has proposed a significant contribution in segmentation process which is the most predominant component of image analysis in constructing the SLR system. Segmentation is handled using edge detection procedure for finding the borders of hand sign within the captured images, by detecting the split in the image illumination. The objective of the edge function, to find the boundary intensity, is done by a particle swarm optimization technique which chooses the optimal threshold values and implemented in the canny hysteresis thresholding method. The analysis primarily uses common edge recognition algorithms which contain Sobel, Robert, Canny and Prewitt from which the scope of the work is extended by introducing an optimization technique in Canny method. The performance of the proposed algorithm is tested with real time Tamil sign language dataset and comparison is inevitably carried out with standard segmentation metrics. Keywords— Tamil Sign Language; Canny Edge Detection; PSO; Thresholding; Objective Function