원문정보
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초록
영어
This paper uses the image entropy directly on the color image to express the integral color image information and color spatial distribution of the neighborhood, then the image is divided into blocks, for each block we use the Pelaez Aggregation to determine the seed, after that we use the regional expansion method for color image blocks to extract the color characteristic of color image. The centroid was extracted from the segmented image and combined with variance as the similarity metric standard. Result shows that, this method is not only simple and efficient, but also improves the performance of image retrieval.
목차
Abstract
1. Introduction
2. The Proposed Algorithm
2.1. The Selection of Color Space
2.2. Quantification of HSV Color Space
2.3. Pretreatment Using Information Entropy
2.4. The Use of Regional Expansion Method
2.5. Criterion of Similarity Measure
3. Experimental Verification
4. Conclusion
Acknowledgements
References
1. Introduction
2. The Proposed Algorithm
2.1. The Selection of Color Space
2.2. Quantification of HSV Color Space
2.3. Pretreatment Using Information Entropy
2.4. The Use of Regional Expansion Method
2.5. Criterion of Similarity Measure
3. Experimental Verification
4. Conclusion
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보