Optimum Uniform Piecewise Linear Approximation of Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Detection of Dominant Points on Digital Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimum polygonal approximation of digitized curves
Pattern Recognition Letters
A new method for polygonal approximation using genetic algorithms
Pattern Recognition Letters
ISE-bounded polygonal approximation of digital curves
Pattern Recognition Letters
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This paper presents a particle swarm optimization algorithm (PSO) to solve error-bounded polygonal approximation of digital curves. Different from the existing PSO-based methods for polygonal approximation problem, the mutation operators borrowed from genetic algorithms, are incorporated into the PSO, so we call it MPSO. This scheme can increase the diversity of the population and help the particles effectively escape from the local optimum. Experiments were performed on three commonly used benchmark curves to test the effectiveness of the proposed MPSO. The results manifest that the proposed MPSO has the higher performance than the existing GA-based methods and PSO methods.