Analyzing hardware constraints of Gabor filtering operation for Facial Expression Recognition System

This paper presents hardware constraints analysis of Gabor filtering operation for its hardware implementation in a real time Facial Expression Recognition System (FERS). Gabor filter is the most common feature extractor employed for the realization of such system. Feature extraction using Gabor filter is efficient and has better discrimination capability. In this work, we have employed software-based approach to find the optimum filter and facial image size. These two factors employed in the Gabor filtering process directly affect the hardware resource utilization and hence we have considered these two factors for our analysis. We have used two versions of Gabor filter for feature extraction, one using the original Gabor filtering approach and the other its modified version using Image Pyramid based approach. Support Vector Machine (SVM) classifier has been used for analyzing the performance of the extracted feature.