CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Fuzzy C Means for Image Batik Clustering based on Spatial Features

by Anita Ahmad Kasim, Retantyo Wardoyo, Agus Harjoko
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 117 - Number 2
Year of Publication: 2015
Authors: Anita Ahmad Kasim, Retantyo Wardoyo, Agus Harjoko
10.5120/20523-2853

Anita Ahmad Kasim, Retantyo Wardoyo, Agus Harjoko . Fuzzy C Means for Image Batik Clustering based on Spatial Features. International Journal of Computer Applications. 117, 2 ( May 2015), 1-4. DOI=10.5120/20523-2853

@article{ 10.5120/20523-2853,
author = { Anita Ahmad Kasim, Retantyo Wardoyo, Agus Harjoko },
title = { Fuzzy C Means for Image Batik Clustering based on Spatial Features },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 117 },
number = { 2 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume117/number2/20523-2853/ },
doi = { 10.5120/20523-2853 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:58:13.028963+05:30
%A Anita Ahmad Kasim
%A Retantyo Wardoyo
%A Agus Harjoko
%T Fuzzy C Means for Image Batik Clustering based on Spatial Features
%J International Journal of Computer Applications
%@ 0975-8887
%V 117
%N 2
%P 1-4
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Patterns of batik produce geometric shapes unique, the number and name of the batik patterns make it difficult to recognize each motif. Spatial information is an important aspect of image processing such as computer vision and recognition structure / pattern in the context of modeling and resolution of the uncertainty caused by the ambiguity in the low-level features. Batik motifs are very diverse produce values that are sometimes not obvious feature class. There is a feature that is included in the value of two different classes. This causes an error in the process of cluster motif. The problems described above can be formulated problem in this research is how to build a cluster of batik images using fuzzy C means cluster based on spatial features. From the results of experiments that have been done obtained Fuzzy C Means able to build a cluster of batik based on the spatial characteristics of contrast, energy, correlation and homogeneity. Cluster obtained seen that the use of FCM in the cluster image Batik produces batik image data distribution in cluster grouping characteristic obvious visible difference.

References
  1. J. Yu, 2010. Texture Image Segmentation Based on Gaussian Mixture Models and Gray Level Co-occurrence Matrix. Third Int. Symp. Inf. Sci. Eng. , no. 1, pp. 149–152
  2. Z. Juanjuan, L. U. Huijun, L. I. Yue, and C. Junjie, 2012. A kind of Fuzzy Decision Tree Based on the Image Emotion Classification. 2012 Int. Conf. Comput. Meas. Control Sens. Netw. , no. 60970059, pp. 167–170
  3. B. Arisandi, N. Suciati, and A. Yudhi. 20121. Introduction to Batik With Rotated Wavelet Filter and Neural Network. Paper Session Final, Institut Teknologi Surabaya.
  4. A. A. Pratama, N. Suciati, and D. Purwitasari. 2012. Implementation of Fuzzy C-Means clustering for image Batik Motif Based on Texture Feature J. Tek. POMITS, vol. 1, no. 1, pp. 1–4.
  5. A. A. Kasim and A. Harjoko, 2014. Clustering Image Batik Using Neural Network Based on Gray Level Co-Occurrence Matrices (GLCM) in Seminar Nasional Teknologi Informasi.
  6. A. A. Kasim and R. Wardoyo. 2013. Batik Image Classification Rule Extraction Using Fuzzy Decision Trees in Information System International Conference (ISICO) Bali.
  7. V. S. Moertini and B. Sitohang. 2005. Algorithms of Clustering and Classifying Batik Images Based on Color, Contrast and Motif," ITB J. Eng. Sci. , vol. 37, no. 2, pp. 141–160
  8. V. S. Moertini. 2005. Towards classifying classical batik images
  9. A. H. Rangkuti. 2014. Content Based Batik Image Classification Using Wavelet Transform And Fuzzy Neural Network J. Comput. Sci. , vol. 10, no. 4, pp. 604–613
  10. A. Gebejes, E. M. Master, and A. Samples. 2013. Texture Characterization based on Grey-Level Co-occurrence Matrix in Conference Of Informatics and MAnagement ICTIC 2013, 2013, pp. 375–378.
  11. J. C. Bezdek, R. Ehrlich, and W. Full. 1984. FCM?: The Fuzzy C-Means Clustering Algorithm Comput. Geosci. , vol. 10, no. 2, pp. 191–203
Index Terms

Computer Science
Information Sciences

Keywords

Cluster Batik Spatial Feature

Powered by PhDFocusTM