Baochang Zhang

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A novel object descriptor, histogram of Gabor phase pattern (HGPP), is proposed for robust face recognition. In HGPP, the quadrant-bit codes are first extracted from faces based on the Gabor transformation. Global Gabor phase pattern (GGPP) and local Gabor phase pattern (LGPP) are then proposed to encode the phase variations. GGPP captures the variations(More)
This paper proposes a novel high-order local pattern descriptor, local derivative pattern (LDP), for face recognition. LDP is a general framework to encode directional pattern features based on local derivative variations. The <i>nth</i>-order LDP is proposed to encode the (<i>n</i>-1)<i>th</i> -order local derivative direction variations, which can capture(More)
This paper introduces the establishment of PolyU near-infrared face database (PolyU-NIRFD) and presents a new coding scheme for face recognition. The PolyU-NIRFD contains images from 350 subjects, each contributing about 100 samples with variations of pose, expression, focus, scale, time, etc. In total, 35,000 samples were collected in the database. The(More)
This paper proposes a new face recognition method, named kernel learning of histogram of local Gabor phase pattern (K-HLGPP), which is based on Daugman’s method for iris recognition and the local XOR pattern (LXP) operator. Unlike traditional Gabor usage exploiting the magnitude part in face recognition, we encode the Gabor phase information for face(More)
In this paper, we introduce the completed local binary patterns (CLBP) operator for the first time on remote sensing land-use scene classification. To further improve the representation power of CLBP, we propose a multi-scale CLBP (MS-CLBP) descriptor to characterize the dominant texture features in multiple resolutions. Two different kinds of(More)
This paper presents a new Sobel-LBP, an extension of existing local binary pattern (LBP), for facial image representation. The face image is filtered by Sobel operator to enhance the edge information. Sobel-LBP feature distributions are then extracted and concatenated into a spatial histogram to be used as a face descriptor. The proposed method is compared(More)
This paper gives fair comparisons of shape and texture based methods for vein recognition. The shape of the back of hand contains information that is capable of authenticating the identity of an individual. In this paper, two kinds of shape matching method are used, which are based on Hausdorff distance and Line Edge Mapping(LEM) methods. The vein image(More)
In this paper, we propose an approach for fast pedestrian detection in images. Inspired by the histogram of oriented gradient (HOG) features, a set of multi-scale orientation (MSO) features are proposed as the feature representation. The features are extracted on square image blocks of various sizes (called units), containing coarse and fine features in(More)