JOURNAL ARTICLE

Image Retrieval Based on Weighted Block Color Histogram and Texton Co-occurrece Matrix

Abstract

Image retrieval is an important topic in the fields of image processing, pattern recognition and computer vision.In this paper, we proposed a new and efficient method of image retreival by combining the color and texture features.We used HSV color histogram for color feature extraction and texton co-occurrence matrix for texture feature extraction.In color feature extraction, the image was divided into nine unequal blocks first and then for each block HSV color histogram was computed.In texture feature extraction, the gray level image was filtered with four predefined textons first and then we used co-occurrence matrix to extract the texture feature of the filtered texton image.After feature extraction, we used Euclidean distance to measure the similarity of the query image and images in the database.We emploied Corel 1000 database for our experiment, the experimental results show that our proposed method performs better than the previous methods.

Keywords:
Artificial intelligence Computer science Pattern recognition (psychology) Histogram Block (permutation group theory) Computer vision Histogram equalization Adaptive histogram equalization Image (mathematics) Mathematics

Metrics

1
Cited By
0.21
FWCI (Field Weighted Citation Impact)
13
Refs
0.62
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

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
Video Analysis and Summarization
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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