%0 Conference Proceedings
%T Image Clustering Using Multi-visual Features
%+ University of Indonesia (UI)
%+ YARSI University
%A Priyogi, Bilih
%A Selviandro, Nungki
%A Hasibuan, Zainal, A.
%A Ahmad, Mubarik
%Z Part 1: Information & Communication Technology-EurAsia Conference 2014, ICT-EurAsia 2014
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 2nd Information and Communication Technology - EurAsia Conference (ICT-EurAsia)
%C Bali, Indonesia
%Y David Hutchison
%Y Takeo Kanade
%Y Bernhard Steffen
%Y Demetri Terzopoulos
%Y Doug Tygar
%Y Gerhard Weikum
%Y Linawati
%Y Made Sudiana Mahendra
%Y Erich J. Neuhold
%Y A Min Tjoa
%Y Ilsun You
%Y Josef Kittler
%Y Jon M. Kleinberg
%Y Alfred Kobsa
%Y Friedemann Mattern
%Y John C. Mitchell
%Y Moni Naor
%Y Oscar Nierstrasz
%Y C. Pandu Rangan
%I Springer
%3 Information and Communication Technology
%V LNCS-8407
%P 179-189
%8 2014-04-14
%D 2014
%R 10.1007/978-3-642-55032-4_18
%K Image Clustering
%K Visual Feature
%K K-Means Clustering
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X This paper presents a research on clustering an image collection using multi-visual features. The proposed method extracted a set of visual features from each image and performed multi-dimensional K-Means clustering on the whole collection. Furthermore, this work experiments on different number of visual features combination for clustering. 2, 3, 5 and 7 pair of visual features chosen from a total of 8 visual features used, to measure the impact of using more visual features towards clustering performance. The result show that the accuracy of multi-visual features clustering is promising, but using too many visual features might set a drawback.
%G English
%Z TC 5
%Z TC 8
%2 https://inria.hal.science/hal-01397191/document
%2 https://inria.hal.science/hal-01397191/file/978-3-642-55032-4_18_Chapter.pdf
%L hal-01397191
%U https://inria.hal.science/hal-01397191
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-TC8
%~ IFIP-ICT-EURASIA
%~ IFIP-LNCS-8407