An efficient method for face recognition under illumination variations

An efficient method for face recognition which is robust under illumination variations is proposed. The proposed method achieves the illumination invariants based on the reflectance-illumination model. Different high-pass filters have been tested to achieve the reflectance part of the image which is illumination invariant and maximum filter is proposed as the best method for this purpose. The proposed method does not require any prior information about the face shape or illumination and can be applied on each image separately and does not need multiple images in training stage to get the illumination invariants. The proposed method is computationally efficient. Support vector machines and k-nearest neighbors method are used as classifier. Several experiments are performed on Yale B and extended Yale B databases. The system achieved 99.30% recognition rate in the Yale B database.

• Type: Journal
• Year: 2010
• Where: IEEEHPCS
• Authors: A. Nabatchian, E. Abdel-Raheem, M. Ahmadi
• Keywords: Applied Computing, IEEEHPCS 2010, Illumination Variations, Images, K-nearest Neighbors Method