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IMAGE RETRIEVAL BY GENERATING A DESCRIPTOR FOR EACH SPOT OF AN IMAGE THE CELLS OF WHICH HAVING VISUAL CHARACTERISTICS WITHIN A SELECTED TOLERANCE
IMAGE RETRIEVAL BY GENERATING A DESCRIPTOR FOR EACH SPOT OF AN IMAGE THE CELLS OF WHICH HAVING VISUAL CHARACTERISTICS WITHIN A SELECTED TOLERANCE
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机译:通过为每个图像的斑点生成描述器以在选定的公差范围内具有视觉特征的细胞
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摘要
A system and method indexes an image database by partitioning an image thereof into a plurality of cells, combining the cells into intervals and then spots according to perceptual criteria, and generating a set of spot descriptors that characterize the perceptual features of the spots, such as their shape, color and relative position within the image. The shape preferably is a derivative of the coefficients of a Discrete Fourier Transform (DFT) of the perimeter trace of the spot. The set of spot descriptors forms as an index entry for the spot. This process repeated for the various images of the database. To search the index, a key comprising a set of spot descriptors for a query image is generated and compared according to a perceptual similarity metric to the entries of the index. The metric determines the perceptual similarity that the features of the query image match those of the indexed image. The search results are presented as a scored list of the indexed images. A wide variety of image types can be indexed and searched, including: bi-tonal, gray-scale, color, “real scene” originated, and artificially generated images. Continuous-tone “real scene” images such as digitized still pictures and video frames are of primary interest. There are stand alone and networked embodiments. A hybrid embodiment generates keys locally and performs image and index storage and perceptual comparison on a network or web server.
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