Spectral covariance and fuzzy regions for image indexing
Machine Vision and Applications
Color and spatial feature for content-based image retrieval
Pattern Recognition Letters
Scalable integrated region-based image retrieval using IRM and statistical clustering
Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
IDEAS '01 Proceedings of the International Database Engineering & Applications Symposium
Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical color image region segmentation for content-based image retrieval system
IEEE Transactions on Image Processing
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Image retrieval has emerged as an important problem in multimedia database management. This paper uses the color distribution, the mean value and the standard deviation, of an image as global information for image retrieval. Furthermore, this paper uses the common bitmap to represent the local characteristics of the image. The performance of the method is tested on three different image databases consisting of 410, 235, and 10,235 images. The third database has been partitioned into 10 categories for exploring the category retrieval ability. According to the experimental results, we find that the proposed method can effectively retrieve more similar images than other methods and the category ability is also higher than others. In addition, the total memory space for saving the image features of the proposed method is less than other methods.