Color-based Segmentation of Batik Using the L*a*b Color Space
DOI:
10.33395/sinkron.v3i2.10102Abstract
Indonesian Batik has a variety of styles. Coloring techniques affect the color quality of batik. Color is very important to show staining breakthroughs. The colors R (Red) G (Green) and B (Blue) have a close color correlation level so that it is difficult to segment. Segmentation is the process of partitioning digital images into several segments. The segmentation process is carried out on 15 batik sample data. The first step, each sample is converted from RGB - XYZ - Lab color. The average ratio of Red, Green and Blue on the RGB color and XYZ color 1:10. Segmentation using L*a*b color, displays the composition of the sample data colors into six clusters: background, yellow, magenta, purple, red and green using the clustering method. This proposed work L*a*b color space is selected which is a homogeneous space for visual perception.
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[2] K. Kavi Niranjana, M. Kalpana Devi, “RGB to Lab Transformation Using Image Segmentation”, International Journal of Advance Research in Computer Science and Management StudiesVolume 3, I ssue 11, pg. 8-16, November 2015.
[3] Dibya Jyoti Bora, Anil Kumar Gupta, Fayaz Ahmad Khan, “Comparing the Performance of L*A*B* and HSV Color Spaces with Respect to Color Image Segmentation”, Volume 5, Issue 2, pp. 192-203, February 2015.
[4] Sukmawati Nur Endah, Retno Kusumaningrum, Helmie Arif Wibawa, “Color Space to Detect Skin Image: The Procedure and Implication”, Scientific Journal of Informatics, Vol. 4, No. 2, pp. 143-149, November 2017.
[5] Mohammad A. Al-Jarrah, “Image Segmentation Utilizing Color-Space Feature”, International Journal of Multimedia Data Engineering and Management, 6(1), 39-53, January-March 2015.
[6] P. Ganesan, V. Rajini, B. S. Sathish, V. Kalist, S. K. Khamar Basha, “Satellite Image Segmentation Based on YCbCr Color Space”, Indian Journal of Science and Technology, Vol 8(1), 35–41, January 2015.
[7] Ramaraj.M, S.Niraimathi, “APPLICATION OF COLOR BASED IMAGE SEGMENTATION PARADIGM ON RGB COLOR PIXELS USING FUZZY C-MEANS AND K MEANS ALGORITHMS”, International Journal of Computer Science and Mobile Computing, Vol.6 Issue.6, pg. 430-440, June- 2017.
[8] Khushbu Raval Ravi Shukla and Ankit KShah “Color Image Segmentation using FCM Clustering Technique in RGB, L*a*b, HSV, YIQ Color spaces”, European Journal of Advances in Engineering and Technology, 4 (3):194-200, 2017.
[9] Md. Rakib Hassan, Romana Rahman Ema & Tajul Islam “Color Image Segmentation using Automated K-Means Clustering with RGB and HSV Color Spaces”, Global Journal of Computer Science and Technology: Graphics & vision, Volume 1 7 Issue 2, January 2017.
[10] Neelambike S, Parashuram Baraki, “Color Image Segmentation By Clustering”, International Journal of Advanced Research in Computer Science & Technology (IJARCST 2014), Vol. 2 Issue 1 95-97, Jan-March 2014.


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