Face recognition based on Extended Symmetric Local Graph Structure

A. Yunanto, D. Herumurti
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引用次数: 3

Abstract

Face recognition is an important area in biometrics and computer vision. A lot of feature extraction can handle face recognition method such as checking pixel neighbor. Local Binary Pattern, Local Graph Structure, and Symmetric Local Graph Structure are an operator of the feature extraction. This research called Extended Symmetric Local Graph Structure which it is an improvement operator from SLGS to build more symmetric neighbor. The result of ESLGS has average accuracy 84.24% in one until five retrieval similarity of YALE dataset image and 80.59% in one until five retrieval similarity of ORL dataset image. The conclusion indicates that our proposed operator has more accuracy than LBP, LGS and SLGS operator. Advantage of proposed method is to provide better performance in accuracy and complexity than other operator.
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基于扩展对称局部图结构的人脸识别
人脸识别是生物识别和计算机视觉中的一个重要领域。许多特征提取可以处理人脸识别的方法,如检查像素邻居。局部二值模式、局部图结构和对称局部图结构是特征提取的算子。该研究被称为扩展对称局部图结构,它是SLGS的改进算子,用于建立更对称的邻居。ESLGS结果对YALE数据集图像的1至5检索相似度平均准确率为84.24%,对ORL数据集图像的1至5检索相似度平均准确率为80.59%。结果表明,本文提出的算子比LBP、LGS和SLGS算子具有更高的精度。该方法的优点是在精度和复杂度方面优于其他算子。
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