Content-Based Image Retrieval using Color Quantization and Angle Representation

Authors

  • Ihab Zaqout Alazhar University – Gaza, Gaza Strip, Palestine

DOI:

https://doi.org/10.24297/ijct.v13i10.2332

Keywords:

Content-based image retrieval, Segmentation, Marker histogram, Non-uniform color quantization, Similarity measurement.

Abstract

An efficient non-uniform color quantization and similarity measurement methods are proposed to enhance the content-based image retrieval (CBIR) applications. The HSV color space is selected because it is close to human visual perception system, and a non-uniform color method is proposed to quantize an image into 37 colors. The marker histogram (MH) vector of size 296 values is generated by segmenting the quantized image into 8 regions (multiplication of 45°) and count the occurrences of the quantized colors in their particular angles. To cope with rotated images, an incremental displacement to the MH is applied 7 times. To find similar images, we proposed a new similarity measurement and other 4 existing metrics. A uniform color quantization of related work is implemented too and compared to our quantization method. One-hundred test images are selected from the Corel-1000 images database. Our experimental results conclude high retrieving precision ratios compared to other techniques.

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Author Biography

Ihab Zaqout, Alazhar University – Gaza, Gaza Strip, Palestine

Department of Information Technology, Faculty of Engineering & Information Technology

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Published

2014-10-30

How to Cite

Zaqout, I. (2014). Content-Based Image Retrieval using Color Quantization and Angle Representation. INTERNATIONAL JOURNAL OF COMPUTERS &Amp; TECHNOLOGY, 13(10), 5094–5104. https://doi.org/10.24297/ijct.v13i10.2332

Issue

Section

Research Articles