Open AccessReal-time Multi-object Face Recognition Using Content Based Image Retrieval (CBIR)
Author(s) -
Muhammad Fachrurrozi,
Saparudin Saparudin,
Erwin Erwin,
Mardiana Mardiana,
Clara Fin Badillah,
Junia Erlina,
Auzan Lazuardi
Publication year - 2018
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v8i5.pp2812-2817
Subject(s) - computer science , pattern recognition (psychology) , artificial intelligence , content based image retrieval , cluster analysis , local binary patterns , euclidean distance , image retrieval , facial recognition system , feature (linguistics) , feature extraction , face (sociological concept) , image (mathematics) , computer vision , histogram , social science , linguistics , philosophy , sociology
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%.