An Object Location Strategy using Shape and Grey-level Models

Abstract Any model-based image interpretation system must be capable of describing objects, whose appearance in real images can vary widely, in sufficient detail to ensure that robust location of objects is possible. The system must cope with circumstances where data is incomplete, for example when touching and occlusion occur. It is argued that to achieve this it is necessary to describe grey-level properties as well as geometric ones, and their expected variations. This paper proposes an object description which combines an explicit shape model with models of expected grey-level boundary appearance together with a mechanism for evaluating image data for correspondences to the model. The results of applying the method to locating the boundaries of overlapping and touching objects in microscope images of metaphase chromosomes and manmade mineral fibres are presented.

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