GENETIC ALGORITHMS FOR ERROR-BOUNDED POLYGONAL APPROXIMATION
2000 ◽
Vol 14
(03)
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pp. 297-314
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Keyword(s):
A new polygonal approximation algorithm, employing the concept of genetic evolution, is presented. In the proposed method, a chromosome is used to represent a polygon by a binary string. Each bit, called a gene, represents a point on the given curve. Three genetic operators, including selection, crossover, and mutation, are designed to obtain the approximated polygon whose error is bounded by a given norm. Many experiments show that the convergence is guaranteed and the optimal or near-optimal solutions can be obtained. Compared with the Zhu–Seneviratne algorithm,24 the proposed algorithm successfully reduced the number of segments under the same error condition in the polygonal approximation.
2013 ◽
Vol 380-384
◽
pp. 1464-1468
2016 ◽
Vol 8
(2)
◽
pp. 99-113
◽
2011 ◽
Vol 2011
◽
pp. 1-7
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2007 ◽
Vol 11
(9)
◽
pp. 1092-1098
◽
2017 ◽
Vol 2
(2)
◽