基于局部纹理描述框架的改进局部方向数字模式:一种新的人脸识别描述符

R. R. Rose, A. Suruliandi, K. Meena
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引用次数: 6

摘要

纹理描述符可以有效地捕捉图像的表面属性。然而,几乎所有可用的局部纹理描述符都使用最近邻来编码纹理模式。而早先提出的局部纹理描述框架LTDF则证明了距离所考虑像素一定距离的8个椭圆采样点对于区分不同人脸图像的重要性。近年来,引入了一种局部纹理描述符,即局部方向数模式LDN,用于对人脸纹理结构的方向信息进行编码。结合LTDF和LDN的概念,提出了一种新的纹理描述符,即基于LTDF的改进局部定向数模式LTDF_MLDN。LTDF_MLDN描述了一个采样点位于不同区域的纹理模式。利用5个基准数据库测试了该系统对人脸识别中不同问题的有效性。实验结果表明,所提出的描述符的有效性优于最先进的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Local texture description framework-based modified local directional number pattern: a new descriptor for face recognition
Texture descriptors effectively capture the surface property of images. However, almost all the available local texture descriptors encode a texture pattern using the closest neighbours. But the local texture description framework LTDF proposed earlier proved the importance of eight sampling points that lie elliptically at a certain distance apart from a pixel under consideration in distinguishing different face images. Recently, a local texture descriptor namely local directional number pattern LDN is introduced to encode the directional information of the structure of a face's texture. Incorporating the concepts of LTDF and LDN, this paper proposes a new texture descriptor namely LTDF-based modified local directional number pattern LTDF_MLDN. LTDF_MLDN describes a texture pattern with the sampling points at dissimilar area. Effectiveness of the system is tested for the different issues in face recognition using five benchmark databases. Experimental results reveal the effectiveness of the proposed descriptor over the state-of-the-art approaches.
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