ArticleEntropy (Basel, Switzerland)2021
A Hybrid Rao-NM Algorithm for Image Template Matching.
Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Parameter-free hybrid RAO algorithm for reactive power optimization.Scientific reports · 2026Article
- A bridge dynamic response analysis and load recognition method using traffic imaging.Scientific reports · 2024Article
- Effective Mean Square Differences: A Matching Algorithm for Highly Similar Sheet Metal Parts.Sensors (Basel, Switzerland) · 2023Article
- An Improved Stereo Matching Algorithm for Vehicle Speed Measurement System Based on Spatial and Temporal Image Fusion.Entropy (Basel, Switzerland) · 2021Article
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Authors and funding
5 authors.
Funding
Abstract
This paper proposes a hybrid Rao-Nelder-Mead (Rao-NM) algorithm for image template matching is proposed. The developed algorithm incorporates the Rao-1 algorithm and NM algorithm serially. Thus, the powerful global search capability of the Rao-1 algorithm and local search capability of NM algorithm is fully exploited. It can quickly and accurately search for the high-quality optimal solution on the basis of ensuring global convergence. The computing time is highly reduced, while the matching accuracy is significantly improved. Four commonly applied optimization problems and three image datasets are employed to assess the performance of the proposed method. Meanwhile, three commonly used algorithms, including generic Rao-1 algorithm, particle swarm optimization (PSO), genetic algorithm (GA), are considered as benchmarking algorithms. The experiment results demonstrate that the proposed method is effective and efficient in solving image matching problems.
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