Mohammad Reza Faraji

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Face recognition under illumination variations is a challenging research area. This paper presents a new method based on the log function and the fractal analysis (FA) to produce a logarithmic fractal dimension (LFD) image which is illumination invariant. The proposed FA feature-based method is a very effective edge enhancer technique to extract and enhance(More)
This study proposes an illumination-invariant face-recognition method called adaptive homomorphic eight local directional pattern (AH-ELDP). AH-ELDP first uses adaptive homomorphic filtering to reduce the influence of illumination from an input face image. It then applies an interpolative enhancement function to stretch the filtered image. Finally, it(More)
Face recognition (FR) is a challenging task in biometrics due to various illuminations, poses, and possible noises. In this paper, we propose to apply a novel neutrosophic set (NS)-based preprocesssing method to simultaneously remove noise and enhance facial features in original face images. We then employ the Tan and Triggs (TT) discriminant method, which(More)
Face recognition under varying illumination is a challenging task. This study proposes a modified version of local directional patterns (LDP), eight LDP (ELDP), to produce an illumination insensitive representation of an input face image. The proposed ELDP code scheme uses Kirsch compass masks to compute the edge responses of a pixel's neighbourhood. Then,(More)
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