期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2007
卷号：7
期号：12
页码：38-44
出版社：International Journal of Computer Science and Network Security
摘要：Content-Based Image Retrieval (CBIR) allows to automatically extracting target images according to objective visual contents of the image itself. Representation of visual features and similarity match are important issues in CBIR. In this paper a novel CBIR method is proposed by exploit the wavelets which represent the visual feature. We use Haar and D4 wavelet to decompose color images into multilevel scale and wavelet coefficients, with which we perform image feature extraction and similarity match by means of F-norm theory. Furthermore, we also provide a progressive image retrieval strategy to achieve flexible CBIR. We tested five categories of color images in the experiments. The retrieval performance of D4 and Haar wavelet is compared with wavelet histograms in terms of recall rate and retrieval speed. Experiment results reflect the importance of wavelets in CBIR and F-norm theory along with progressive retrieval strategy achieves efficient retrieval.
