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Communication Dans Un Congrès Année : 2014

Local binary patterns preprocessing for face identification/verification using the VanderLugt correlator

Thibault Napoléon
Ayman Alfalou

Résumé

The face recognition tasks can be divided into two categories: verification (i.e. compare two images in order to know if they represent the same person) and identification (i.e. find the identity of a person into the data-base). Several powerful face recognition methods exist, in literature, for controlled environments: constrained illumination, frontal pose, neutral expression... However, there are few reliable methods for the uncontrolled case. Optical correlation has shown its interest through relevant architectures for controlled and uncontrolled environments. Based on this architecture, we propose a novel method for verification and identification tasks under illumination variation conditions. More specifically, we optimize the performances of a correlation method against illumination changes by using and adapting the Local Binary Patterns (LBP) description. This later is widely used in the literature to describe the texture of an image using 8 bits words. For both, target image and reference image, we begin by using a specific-Gaussian function as first step of LBP-VLC correlator. This function filters the considered image with a band-pass filter in order to extract the edges. Then we applied the adapted LBP-VLC method. To validate our new approach, we used a simple POF filter (others correlation filters can be used). The simulations are done using the YaleB and YaleB Extended databases that contain respectively 10 and 38 identities with 64 illuminations. The results obtained reach more than 94% and 92% for the verification and 93% and 90% for the identification case. These results show the good performances of our approach of LBP-correlation methods against illumination changes.
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Dates et versions

hal-02562736 , version 1 (04-05-2020)

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Thibault Napoléon, Ayman Alfalou. Local binary patterns preprocessing for face identification/verification using the VanderLugt correlator. Pattern Recognition and Tracking, May 2014, Baltimore, United States. pp.909408, ⟨10.1117/12.2051267⟩. ⟨hal-02562736⟩
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