文章基本信息

标题：Real-time Multi-object Face Recognition Using Content Based Image Retrieval (CBIR)
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作者：Muhammad Fachrurrozi ; Saparudin Saparudin ; Erwin Erwin 等
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2018
卷号：8
期号：5
页码：2812-2817
DOI：10.11591/ijece.v8i5.pp2812-2817
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Face recognition system in real time is divided into three processes, namely feature extraction, clustering, detection, and recognition. Each of these stages uses different methods, Local Binary Pattern (LBP), Agglomerative Hierarchical Clustering (AHC) and Euclidean Distance. Multi-face image search using Content Based Image Retrieval (CBIR) method. CBIR performs image search by image feature itself. Based on real time trial results, the accuracy value obtained is 61.64%.
其他摘要：Face recognition system in real time is divided into three processes, namely feature extraction, clustering, detection, and recognition. Each of these stages uses different methods, Local Binary Pattern (LBP), Agglomerative Hierarchical Clustering (AHC) and Euclidean Distance. Multi-face image search using Content Based Image Retrieval (CBIR) method. CBIR performs image search by image feature itself. Based on real time trial results, the accuracy value obtained is 61.64%.
关键词：Face Recognition;LBP;AHC;Real-time;Multi-object;CBIR;Euclidean Distance