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The face recognition system of intelligent anti-theft door by the embedded processor S3C6410 platform drive USB camera to capture the face data, it uses AdaBoost algorithm for detecting and classifying face region gradually in Opencv face database. And then, it uses Local Binary Pattern (LBP) operator with LBP image coding to describe the texture feature of local area which can extract facial feature...
Robust face recognition under uncontrolled illumination conditions is an important problem for real face recognition systems. In this paper, we introduce a novel illumination-robust local descriptor named Sparse Linear Regression Binary (SLRB) descriptor. The SLRB descriptor is a bit string by binarizing the sparse linear regression coefficients in a local block. It is an illumination-insensitive...
Local ternary pattern (LTP) is a noise-robust version of local binary pattern (LBP). They are both encoding for the differences between the intensity of the center pixel and its neighborhoods. In this paper, based on Webers law we propose two new local descriptors, named Weber binary pattern (WBP) and Weber ternary pattern (WTP), which utilize binary and ternary encoding separately for the evaluation...
Robust face recognition under uncontrolled illumination conditions is one of the key challenges for real-time face recognition systems. Weber-face (WF) is an illumination insensitive face representation based on Weber׳ law. In this letter, we develop a generalized Weber-face (GWF) which extracts the statistics of multi-scale information from face images. By assigning different weights to the inner-ground...
This paper proposes a novel face image descriptor local surface pattern (LSP) for illumination-robust face recognition. It is assumed that the discrete array of pixel values comes about by sampling an underlying smooth surface on the domain of the image. The proposed method efficiently estimates the underlying local surface information, which is approximately represented as linear projection coefficients...
Existing face recognition systems can achieve high recognition rates in the well-controlled environment. However, when the resolution of the test images is lower than that of the gallery images, the performance degrades seriously. Traditional two-step solutions (first adopting super-resolution (SR) method, and then performing the recognition phase) mainly focus on visual enhancement, rather than classification...
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