Abstract
The problem of 2-D shape description, particularly with contour partitioning, grouping, and classification in terms of straight and curved, based on the minimum description length (MDL) criterion and shape-fitting techniques, is discussed. The MDL criterion is used to detect outliers in connection with shape fitting. Using the MDL criterion, it is possible to derive for a given data set and a class of models a description which best explains the data. A new algorithm for fitting 2-D points to an ellipse is presented. >
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