Feature selection and reduction for batik image retrieval

Hisyam Fahmi, Remmy A.M. Zen, Hadaiq R. Sanabila, Ida Nurhaida, Aniati Murni Arymurthy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Batik is the fabric which is truly unique to Indonesia. Batik image retrieval is the research area which focuses on image processing and image retrieving based on its characteristics. This study investigated the performance of the feature selection and reduction on the batik retrieval process. The feature employed in this experiment is the combination of four feature extraction methods, which are Gabor filter, log-Gabor filter, GLCM, and LBP. SFFS methods is used to carry out the selection of features, meanwhile, PCA is used to perform the reduction feature. Based on the experiment, PCA can increase the precision about 17%. Meanwhile, SFFS can improve the execution time 1800 times faster.

Original languageEnglish
Title of host publicationProceedings of 2016 5th International Conference on Network, Communication and Computing, ICNCC 2016
PublisherAssociation for Computing Machinery
Pages47-52
Number of pages6
ISBN (Electronic)9781450347938
DOIs
Publication statusPublished - 17 Dec 2016
Event5th International Conference on Network, Communication and Computing, ICNCC 2016 - Kyoto, Japan
Duration: 17 Dec 201621 Dec 2016

Publication series

NameACM International Conference Proceeding Series

Conference

Conference5th International Conference on Network, Communication and Computing, ICNCC 2016
CountryJapan
CityKyoto
Period17/12/1621/12/16

Keywords

  • Batik retrieval
  • Feature reduction
  • Feature selection
  • Principal Component Analysis
  • Sequential Forward Floating Selection

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