An Efficient Implementation of Weighted Fuzzy Fisherface Algorithm for Face Recognition Using Wavelet Transform

Abstract

Problem statement: The paper addresses the face recognition problem by proposing Weighted Fuzzy Fisherface (WFF) technique using biorthogonal transformation. The weighted fuzzy fisherface technique was an extension of Fisher Face technique by introducing fuzzy class membership to each training sample in calculating the scatter matrices. Approach: In weighted fuzzy fisherface method, weight emphasizes classes that were close together and deemphasizes the classes that are far away from each other. Results: The proposed method was more advantageous for the classification task and its accuracy was improved. Also with the performance measures False Acceptance Rate (FAR), False Rejection Rate (FRR) and Equal Error Rate (EER) were calculated. Conclusion: Weighted fuzzy fisherface algorithm using wavelet transform can effectively and efficiently used for face recognition and its accuracy is improved.