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Similarity measures for histological image retrieval

Lam, RWK, Ip, HHS, Cheung, KKT, Tang, LHY and Hanka, R (2000) Similarity measures for histological image retrieval Proceedings - International Conference on Pattern Recognition, 15 (2). pp. 295-298.

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A Gastro-intestinal (GI) Tract histological image is usually composed of texture components with different dimensions and properties. To analyze a histological image, we divide it into an array of sub-images. A feature vector comprising a set of Gabor filters and the intensity statistics is computed in order to classify each sub-image to one of 63 histological labels. To retrieve an image from the database, we compare three similarity measures, shape, neighbour and sub-image frequency distribution. It is found that both neighbour and sub-image frequency distribution similarity measures perform similarly well but the shape similarity measure yields the worst result when retrieving images of different GI tract organs. In general, the sub-image frequency distribution measure is the best choice because it requires less time to compute than the neighbour measure. © 2000 IEEE.

Item Type: Article
Divisions : Surrey research (other units)
Authors : Lam, RWK, Ip, HHS, Cheung, KKT, Tang, LHY and Hanka, R
Date : 1 December 2000
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 11:47
Last Modified : 24 Jan 2020 21:16

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