Optimized polygonal approximation by dominant point deletion

An algorithm for polygonal approximation based on dominant point (DP) deletion is presented in this paper. The algorithm selects an initial set of DPs and starts eliminating them one by one depending upon the error associated with each DP. The associated error value is based on global measure. A local optimization of few neighboring points is performed after each deletion. Although the algorithm does not guarantee an optimal solution, the combination of local and global optimization is expected to produce optimal results. The algorithm is extensively tested on various shapes with varying number of DPs and error threshold. In general, optimal results were observed for about 96% of the times. A good comparative study is also presented in this paper