Abstract
Adaptive Multiple Layer Retinex-Enabled Color Face Enhancement for Deep Learning-Based Recognition
Highlights
In recent years, face recognition has become a popular research topic of computer vision, pattern recognition, and machine learning due to its essential role in real-world applications
EXPERIMENTAL RESULTS AND DISCUSSION we implemented experiments to demonstrate the performance of our proposed method in color face image enhancement
The performance of the proposed method is further compared with other effective previous methods, namely, ASVDF [14], ASVDW [15], FIN-generative adversarial network (GAN) [19], GRIR [35], and to demonstrate the high performance of our proposed method for face recognition
Summary
Face recognition has become a popular research topic of computer vision, pattern recognition, and machine learning due to its essential role in real-world applications. Many challenges remain that affect the high performance of a human face recognition system [1]. These challenges are caused mainly by the significant variations in facial expression, viewpoint, illumination conditions, noise, etc. The quality of the observed face image is severely affected by the illumination variation Even it is nearly impossible for human visual to judge the identity of the face images under harsh illumination conditions. This problem is unavoidable in human face recognition systems in real-world applications, such as public security, social multimedia, or intelligent systems. Illumination compensation of the face image is a practical approach to eliminate lighting variations before face recognition. [3]
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