Curve fitting by rational cubic Bézier with C1 and G1 continuity using metaheuristics methods
Rational cubic Bézier curves are used to approximate the data sets while minimizing the least-squares error function using different metaheuristics algorithms. Those metaheuristics algorithms are Harmony Search, Genetic Algorithm, Particle Swarm Optimization and Modified Harmony Search. This scheme...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
AIP Publishing
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/27856/7/Curve%20fitting%20by%20rational%20cubic%20B%C3%A9zier%20with%20C1%20and%20G1%20continuity%20using%20metaheuristics%20methods.pdf |
| Summary: | Rational cubic Bézier curves are used to approximate the data sets while minimizing the least-squares error function using different metaheuristics algorithms. Those metaheuristics algorithms are Harmony Search, Genetic Algorithm, Particle Swarm Optimization and Modified Harmony Search. This scheme is implemented with continuity of C1 and G1. The comparative and analysis behaviour between the two conditions for the curve fitting on four outline of the test images boundary will be discussed. Based on the analysis, Modified Harmony Search algorithms is more stable, accurate and precise compared to other algorithms, and G1 continuity condition leads to a better curve fit compared to C1. |
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