• Dr. Jageshwar K. Keche
• Mr. Palash P. Feddewar
• Prof. Mahendra P. Dhore

Face recognition technology has become increasingly significant in various applications, including security systems, personal identification, and social media tagging. However, the effectiveness of face recognition systems heavily relies on the quality of feature extraction techniques employed. This paper addresses the challenges faced in accurate face recognition, such as variations in lighting, pose, and expression, which can significantly hinder performance. We explore several prominent feature extraction methods, including Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Gabor Wavelets, Local Binary Patterns (LBP), and advanced techniques utilizing Convolutional Neural Networks (CNNs)[1-4]. Through rigorous experimentation on standard datasets, we evaluate the effectiveness of each method in terms of accuracy and computational efficiency. Our results indicate that while traditional methods like PCA and LDA provide reasonable accuracy, deep learning approaches such as CNNs [2-3] outperform them by leveraging hierarchical feature representation, thereby achieving superior recognition rates. This paper contributes to the ongoing research in face recognition by providing insights into the strengths and weaknesses of various feature extraction techniques and suggesting future directions for enhancing recognition performance.

Face Recognition, Feature Extraction, Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Gabor Wavelets, Local Binary Patterns (LBP), Convolutional Neural Networks (CNNs), Deep Learning.

"A Novel Approach to Feature Extraction Technique for Human Face Recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 10, page no.c679-c686, October-2024, Available :http://www.jetir.org/papers/JETIR2410371.pdf

"A Novel Approach to Feature Extraction Technique for Human Face Recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 10, page no. ppc679-c686, October-2024, Available at : http://www.jetir.org/papers/JETIR2410371.pdf