Local Directional Pattern (LDP) for face recognition

Jabid, Taskeed; Kabir, Md. Hasanul; Chae, Oksam

doi:10.1109/icce.2010.5418801

Cited by 251 publications

(135 citation statements)

References 5 publications

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“…LDA generates variance face with linearity, homogeneity and normality. These features can produce accurate classification if the variance face is represented by a collection of Local Directional Pattern (LDA) codes for face recognition [23]. The minor difference between PCA and LDA is that, PCA is based on encoding information into an orthogonal linear space, while LDA is based on encoding discriminating information into a linearly separable space.…”

Section: Related Workmentioning

confidence: 99%

Face recognition system based on principal components analysis and distance measures

Goyal¹,

Meenpal²

2018

IJET

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Face recognition plays a vital role and has a huge scope in the field of biometrics, image processing, artificial intelligence, pattern recognition and computer vision. This paper presents an approach to perform face recognition using Principal Components Analysis (PCA) as feature extraction technique and different distance measures as matching techniques. The proposed method is developed after the deep study of a number of face recognition methods and their outcomes. In the proposed method, Principal Components Analysis is used for facial features extraction and data representation. It generates eigenvalues of the facial images, hence, reduces the dimensionality. The recognition is produced using three different matching techniques (Euclidean, Manhattan and Mahalanobis) and the results are` presented. Yale and Aberdeen Face Databases are used to test and analyze the results of the proposed method.

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Section: Related Workmentioning

confidence: 99%

Face recognition system based on principal components analysis and distance measures

Goyal¹,

Meenpal²

2018

IJET

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“…LDP operator is a texture characterization method proposed by Jabid et al [13] based on the Local Binary Pattern (LBP). For a 3 × 3 rectangular block, the LDP value at its center is calculated as: Firstly, the edge response values in eight directions (m0 ... m7) are obtained using the Kirsch operators in eight directions (M0 ... M7, as shown in Fig.…”

Section: The Proposed Methodsmentioning

confidence: 99%

“…Shojaiee et al [12] proposed a method named Local Composition Derivative Pattern (LCDP) that gets the direction information missed in the LBP by extracting the first derivative in the radial and other directions in an image. Based on LBP method, Jabid et al [13] proposed a new image texture characterization method called Local Direction Pattern (LDP), which has been successfully used in face recognition. Combining the advantages of Gabor wavelet and LDP, this paper presents a novel palmprint recognition method, named Gabor Local Direction Pattern (G-LDP).…”

Section: Introductionmentioning

confidence: 99%

A Palmprint Recognition Method Based on Gabor Wavelet and Local Direction Pattern

Yu¹,

Xie²

2015

Advances in Intelligent Systems Research

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Abstract. Palmprint recognition is an emerging biometric technology that identifies a person based on the hand image. In this paper, a novel palmprint identification method based on Gabor wavelets and Local Direction Pattern (LDP) techniques has been proposed. The Gabor response images at different scales and directions are obtained by convolving the multi-channel Gabor wavelet and palmprint images, which are further divided into non-overlapping sub-blocks. The LDP characteristics are extracted from each sub-block and the feature vector of palmprint image is then produced by combining them using the LDP operator. Finally, the palmprint images are identified using the nearest neighbor classification method. The proposed method has been verified on the public PolyU palmprint database, and the experimental results have shown that the proposed method is effective.

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“…Local Directional Pattern [15] is a method based on LBP which uses the edge response values of neighborhood pixels to encode the texture in an image. It assigns an eight bit binary code to each pixel of an input image.…”

Section: Local Directional Pattern (Ldp)mentioning

confidence: 99%

Combination of Color and Local Patterns as a Feature Vector for CBIR

KoteswaraRao¹,

Rao²

2014

IJCA

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The local properties of an image can be acquired in many ways. Local Binary Patterns(LBP) operator is one among them in which a centre pixel is referenced with the neighboring pixels to obtain a feature vector. However, the directions are not considered in this method. The Directional Local Extrema Patterns(DLEP) are used to encode the relationship between the reference pixel and its neighbors by computing the edge information in four directions .In this paper, we propose a new approach based on the combination of DLEP and color to derive the properties those can be used in the process of retrieval.

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Local Directional Pattern (LDP) for face recognition

Cited by 251 publications

References 5 publications

Face recognition system based on principal components analysis and distance measures

Face recognition system based on principal components analysis and distance measures

A Palmprint Recognition Method Based on Gabor Wavelet and Local Direction Pattern

Combination of Color and Local Patterns as a Feature Vector for CBIR

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