Research Article Open Access


A. Haris Rangkuti1, Agus Harjoko2 and Agfianto Eko Putro2
  • 1 University of Bina Nusantara, Indonesia
  • 2 University of Gadjah Mada, Indonesia


Content Based Batik Image Retrieval (CBBIR) is an area of research that focuses on image processing based on characteristic motifs of batik. Basically the image has a unique batik motif compared with other images. Its uniqueness lies in the characteristics possessed texture and shape, which has a unique and distinct characteristics compared with other image characteristics. To study this batik image must start from a preprocessing stage, in which all its color images must be removed with a grayscale process. Proceed with the feature extraction process taking motifs characteristic of every kind of batik using the method of edge detection. After getting the characteristic motifs seen visually, it will be calculated by using 4 texture characteristic function is the mean, energy, entropy and stadard deviation. Characteristic function will be added as needed. The results of the calculation of characteristic functions will be made more specific using the method of wavelet transform Daubechies type 2 and invariant moment. The result will be the index value of every type of batik. Because each motif there are the same but have different sizes, so any kind of motive would be divided into three sizes: Small, medium and large. The perfomance of Batik Image similarity using this method about 90-92%.

Journal of Computer Science
Volume 10 No. 6, 2014, 925-934


Submitted On: 7 November 2013 Published On: 27 January 2014

How to Cite: Rangkuti, A. H., Harjoko, A. & Putro, A. E. (2014). CONTENT BASED BATIK IMAGE RETRIEVAL. Journal of Computer Science, 10(6), 925-934.

  • 11 Citations



  • Batik
  • Motif
  • Wavelet Transform
  • Daubechies
  • Edge Detection
  • Grayscale
  • Feature Extraction
  • Texture