Heydi Mendez Vazquez

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—Great progress has been achieved in face recognition in the last three decades. However, it is still challenging to characterize the identity related features in face images. This paper proposes a novel facial feature extraction method named Gabor Ordinal Measures (GOM), which integrates the distinctiveness of Gabor features and the robustness of ordinal(More)
In this paper, the performance of Local Binary Patterns method is evaluated in face recognition with long-wave infrared images. Long-wave infrared images are invariant to illumination conditions, but at the same time are affected by a fixed-pattern noise inherent to this technology. The fixed-pattern noise usually is compensated with a non-uniformity(More)
This paper proposes a new image representation method named Histograms of Gabor Ordinal Measures (HOGOM) for robust face recognition. First, a novel texture descrip-tor, Gabor Ordinal Measures (GOM), is developed to inherit the advantages from Gabor features and Ordinal Measures. GOM applies Gabor filters of different orientations and scales on the face(More)
Face recognition under varying lighting conditions remains an unsolved problem. In this work, a new photometric normalisation method based on local Discrete Cosine Transform in the logarithmic domain is proposed. The method is experimentally evaluated and compared with other algorithms, achieving a very good performance with a total error rate very similar(More)
Feature extraction is critical to the success of a face recognition system. Local Binary Patterns (LBP), with its different extensions, is one of the most popular texture de-scriptors, because of its demonstrated accuracy and efficiency. A LBP code is jointly determined by a number of local comparisons between a central pixel and its surrounding pixels.(More)
Local Binary Patterns (LBP) is one of the most used methods in face recognition. This paper presents a different way of obtaining the regions that are used to construct the LBP histograms, in order to improve its performance in front of illumination problems. The proposed method takes into account the shape of the face to build a triangular mesh in which a(More)
Feature extraction plays an important role in face recognition. Based on local binary patterns (LBP), we propose a novel face representation method which obtains histograms of semantic pixel sets based LBP (spsLBP) with a robust code voting (rcv). By clustering according the semantic pixel relations before the histogram estimation, the spsLBP makes better(More)