Multi-object face recognition using Content Based Image Retrieval (CBIR)

M. Fachrurrozi, Erwin, Saparudin, Mardiana
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引用次数: 24

Abstract

Real-time face recognition system process divided into three steps, feature extraction, clustering, detection, and recognition. Each step uses a different method that is Local Binary Pattern (LBP), Agglomerative Hierarchical Clustering (AHC) and Euclidean Distance. Content Based Image Retrieval (CBIR), an image searching techniques based on image feature, is implemented as the searching method. Based experiments and the testing result, recall and precision values are 65.32% and 64.93% respectively.
基于内容图像检索(CBIR)的多目标人脸识别
实时人脸识别系统的过程分为三个步骤,特征提取、聚类、检测和识别。每一步使用不同的方法,即局部二值模式(LBP)、聚类层次聚类(AHC)和欧几里得距离。基于内容的图像检索(CBIR)是一种基于图像特征的图像检索技术。基于实验和测试结果,查全率和查准率分别为65.32%和64.93%。
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