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A novel local texture feature extraction method called multi-direction local binary pattern

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Abstract

A novel method named MD-LBP (Multi-Direction Local Binary Pattern) is proposed in this paper to capture the excellent local texture features. Based on LBP (Local Binary Pattern), the proposed method is a local feature extraction method, which optimized the coding scheme by considering the relationship between the center pixel and the weighted pixels in its neighborhood. Furthermore, unlike the original gray scale histogram method, the proposed method used a new way to get the feature vector which not only describes the holistic spatial information of image, but also reduces the image dimension. The proposed method is evaluated by extensive experiments on benchmark databases, such as CMU PIE and Extended Yale B face database, PolyU and CASIA Palmprint database. The experimental results show that the proposed method MD-LBP, can significantly capture the useful local texture features, and improve the recognition rates both in face and palmprint fields.

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Acknowledgments

We would like to thank the associate editor and all anonymous reviewers for their constructive comments and suggestions. And portions of the research in this paper use the CASIA Palmprint Database collected by the Chinese Academy of Sciences’ Institute of Automation (CASIA). This research was partially supported by the National Science Foundation of China (Grant No. 61101246) and the Fundamental Research Funds for the Central Universities (Grant No. JB150209).

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  1. School of Electronic Engineering, Xidian University, Xi’an, 710071, China

    Jin Liu, Yue Chen & Shengnan Sun

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  1. Jin Liu
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  2. Yue Chen
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  3. Shengnan Sun
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Correspondence to Jin Liu.

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Liu, J., Chen, Y. & Sun, S. A novel local texture feature extraction method called multi-direction local binary pattern. Multimed Tools Appl 78, 18735–18750 (2019). https://doi.org/10.1007/s11042-018-7095-x

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