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Content-Based Image Retrieval using Color Quantization and Angle Representation

Journal: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY (Vol.13, No. 10)

Publication Date:

Authors : ;

Page : 5094-5104

Keywords : Content-based image retrieval; Segmentation; Marker histogram; Non-uniform color quantization; Similarity measurement.;

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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.

Last modified: 2016-06-29 16:52:36