Transactions on Mass-Data Analysis of Images and Signals (ISSN:1868-6451)
Volume 1 - Number 2 - September 2009 - Pages 198-209
Learning of Shape Models from Exemplars of Biological Objects in Images
P. Perner and S. Jšnichen
IBaI, Leipzig, Germany
Model-based image recognition requires a general model of the object that should be detected in an image. In many applications such models are not known a-priori instead of they must be learnt from examples. Real world applications such as the recognition of biological objects in images cannot be solved by one general model but a lot of different models are necessary in order to handle the natural variations of the appearance of the objects of a certain class. Therefore we are talking about case-based object recognition. In this paper we describe how the shape of an object can be extracted from images and input into a case description. These acquired number of cases we mine for more general shapes so that at the end a case base of shapes can be constructed and applied for case-based object recognition.