An Optical Machine Vision System for Applications in Cytopathology

Abstract — This paper discusses a new approach to the pro-cesses of object detection, recognition and classification in a digital image focusing on problem in Cytopathology. A unique self learning procedure is presented in order to incorporate expert knowledge. The classification method is based on the application of a set of features which includes fractal parameters such as the Lacunarity and Fourier dimension. Thus, the approach includes the characterisation of an object in terms of its fractal properties and texture characteristics. The principal issues associated with object recognition are presented which include the basic model and segmentation algorithms. The self-learning procedure for designing a decision making engine using fuzzy logic and mem-bership function theory is also presented and a novel technique for the creation and extraction of information from a membership function considered. The methods discussed and the algorithm