CBIR System using Color Moment and Color Auto-Correlogram with Block Truncation Coding

نویسندگان

  • Vandana Vinayak
  • Sonika Jindal
  • Meenakshi Garg
  • Amit Singla
  • Martha Saenz
  • Edward J. Delp
  • Dipankar Hazra
  • Hong-Jiang Zhang
  • Jufu Feng
  • Hui Yu
  • Mingjing Li
  • Olli Nevalainen
  • Pasi Franti
  • Richard E. Woods
  • Rafael C. Gonzalez
چکیده

In content-based Image Retrieval (CBIR) application, a large amount of data is processed. Among various low-level features like color, shape and texture, color is an important feature and represented in the form of histogram. It is essential that features required to be coded in such a way that the storage space requirement is low and processing speed is high. In this paper, we propose a method for indexing of images in the large database with lossy compression technique known as Block Truncation Coding (BTC) along with two different color feature extraction methods Color Moment and Color Auto-correlogram. Block truncation coding divided the original image into multiple non-overlapping blocks and then retrieve the required features. The proposed method performs better.

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تاریخ انتشار 2017