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Accumulation methods in the processing of difficult images

Chmielewski L.J.

Journal of Medical Informatics & Technologies

2008

Vol. 12

11--21

The accumulation methods emerged in close relation to the development of the Hough transform (HT). The application of some far reaching generalizations of the HT will be presented. The accumulation principle will be taken as a starting point: Accumulate the relevant data from possibly many, possibly competent sources. This principle is known and widely used in image processing, mainly in the methods related to the HT. The principle is in opposition to the tendency to compress the image data as early in the processing as possible. The accumulation principle is a recommendation to utilize the redundancy in the image data in a specific way and should be applied when the images are difficult to process due to their low quality. The basic data structure is the fuzzy histogram, which is in fact an experimentally obtained approximation of the probability density of the phenomenon of interest. The concepts of a degree of fuzzification and the weakly and strongly fuzzified histograms will be introduced. A number of solutions found with the use of the accumulation principle will be presented. In the examples and tests, biomedical images will be used. Such images are challenging because the objects imaged are irregular and the quality of the images is usually limited in a natural way by the imaging modalities used. The accumulation methods are a good solution to the problem of analysis of such images.