JOURNAL ARTICLE

Segmentation-Based Image Retrieval

Abstract

Color features are important to pictures and they are easy to calculate. Therefore, the features are widely used in content-based image retrieval (CBIR)[4][7]. In the meantime, it lacks space information. In this paper, color spaces are analyzed and YUV color space is chosen. Color and texture features are extracted in segmentation block, so there are space information. Major color, major segmentation block, a new kind of color quantization and a new Gray scale co-existing matrix's method are proposed. Our approach is described in detail and compared with other methods presented in the literature to deal with the same problem. The experiments are finished and show that the method in this paper is effective and efficient.

Keywords:
Artificial intelligence Computer science Color quantization Color space Computer vision Image texture Image retrieval Image segmentation Color histogram Color image Segmentation Pattern recognition (psychology) Block (permutation group theory) Image (mathematics) Image processing Mathematics

Metrics

2
Cited By
0.60
FWCI (Field Weighted Citation Impact)
11
Refs
0.72
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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