Decomposition of color images into singular components
DOI:
https://doi.org/10.15587/1729-4061.2013.16652Keywords:
image segmentation, context image retrieval, singular image decomposition, context region-based retrievalAbstract
Image segmentation is widely used in the systems of context region-based image retrieval (RBIR). For the RBIR system implementation first of all it is necessary to develop an image automatic annotation subsystem, namely to represent an image as a set of semantically separate regions. For solving this problem the method of image decomposition into singular components corresponding to three largest eigenvalues, which contain information about largescale regions, is proposed. The method, based on the analysis of eigenvectors, was proposed for automatic determining the number of regions or large-scale color clusters. It is shown, that the number of clusters is equal to the number of sign inversions of the component of eigenvector, corresponding to the third eigenvalue, in the order of descending sequence of singular valuesReferences
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- Sural, S., Qian, G., & Pramanik, S. (2002). Segmentation and histogram generation using the HSV color space for image retrieval. Proceedings of IEEE International Conference on Image Processing, 589–592.
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- Martin, D., Fowlkes, C., & Tal, D., & Malik, J. (2001). A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics. Proceedings 8th Intel Conference Computer Vision, 2, 416−423
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