원문정보
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초록
영어
Image Retrieval is the basic requirement of today’s life in present scenario. Because of huge amount of different types of images are added in database from different sources for retrieval of the image, different kinds of processing is required to extract the relevant features from them. In this paper, comparisons of combination texture and shape features are done with texture Gray Level Co- occurrence Matrix and Hu-moments and the combination of tamura texture and shape invariant Hu- moments. For the performance evaluation of the system we use most commonly used methods namely precision and recall.
목차
Abstract
1. Introduction
2. Related Work in this Field
3. Feature Extraction
3.1. Feature Extraction Based on Texture
3.2. Feature Extraction Based on Shape
4. Proposed Methodology
4.1. Algorithm for Proposed Methodology
5. Similarity Measurement
6. Experimental Results
7. Conclusion
References
1. Introduction
2. Related Work in this Field
3. Feature Extraction
3.1. Feature Extraction Based on Texture
3.2. Feature Extraction Based on Shape
4. Proposed Methodology
4.1. Algorithm for Proposed Methodology
5. Similarity Measurement
6. Experimental Results
7. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보