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The Human Facial Expression Recognition is used in many fields such as mood detection and Human Computer Interaction (HCI). Gabor Filters are used to extract features. Gabor has the useful property of robustness against slight object rotation, distortion and variation in illumination. In the present work the effort has been made to provide the modules of for Human facial expression recognition by reducing the number of parameters use to represent Gabor feature the space complexity can reduce. SVM classifier has multi-classes. SVM classifies the expression by comparing it with the trained data.

Human Facial Expression Recognition using Gabor Filter Bank with Minimum Number of Feature Vectors