Design of Perimeter Estimators for Digitized Planar Shapes
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Measurement of perimeters of planar shapes from their digitized images is an important task of computer vision systems. A general methodology for the design of simple and accurate parameter estimation algorithms is described. It is based on minimizing the maximum estimation error for digitized straight edges over all orientations. Two perimeter estimators are derived and their performance is tested and digitized circles using computer simulations. The experimental results may be used to predict the performance of the algorithm on shapes with arbitrary contours of continuous curvature. The simulations also show that fast and accurate perimeter estimation is possible, even for objects that are small relative to pixel size.
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Index Terms:
computerised picture processing; pattern recognition; perimeter estimators; digitized planar shapes; computer vision; design; estimation error; shapes; arbitrary contours; continuous curvature; computer vision; computerised pattern recognition; computerised picture processing; optimisation; parameter estimation
Citation:
J. Koplowitz, A.M. Bruckstein, "Design of Perimeter Estimators for Digitized Planar Shapes," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, no. 6, pp. 611-622, June 1989, doi:10.1109/34.24795
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