지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2013.6
- 수록면
- 155 - 165 (11page)
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초록· 키워드
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Content-based image retrieval (CBIR) deals with the retrieval of most similar images corresponding to a query image from an image database by using visual contents of the image itself. It requires feature extraction and computation of similarity. In this paper, we propose a content-based image retrieval method that uses a combination of color and texture features. The Haar wavelet transform is used for texture feature extraction, and for color feature extraction we use color moments. The distance between the query image features and the database images’ features is computed by using Canberra distance. We assign weights to texture feature distance and color feature distance and calculate the similarity with combined feature distance. Experiment results reflect the importance of the Haar wavelet transform and color moments in the performance of our proposed CBIR method.
목차
Abstract
Introduction
Related Work
Proposed Method
Experiments and Results
Conclusion
References
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UCI(KEPA) : I410-ECN-0101-2015-500-002466468