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- W2751293135 abstract "In the Image Processing (IP) domain, optimization algorithms have to be applied in many cases. Nature-inspired heuristics allow obtaining near optimal solutions using lower computing resources. In this paper the Fireworks Algorithm (FWA) behavior is studied for Image Registration (IR) problems. The IR results accuracy is analyzed for different types of images, mainly in case of pixel based registration using the Normalized Mutual Information. FWA is compared to Particle Swarming (PSO), Cuckoo Search (CSA) and Genetic Algorithms (GA) in terms of results accuracy and number of objective function evaluations required to obtain the optimal geometric transform parameters. Because the pixel based IR may fail in case of images containing graphic drawings, a features based IR approach is proposed for this class of images. Comparing to other nature inspired algorithms, FWA performances are close to those of PSO and CSA in terms of accuracy. Considering the required computing time, that is determined by the number of cost function evaluations, FWA is little slower than PSO and much faster than CSA and GA." @default.
- W2751293135 created "2017-09-15" @default.
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- W2751293135 date "2017-09-02" @default.
- W2751293135 modified "2023-09-24" @default.
- W2751293135 title "Fireworks Algorithm Based Image Registration" @default.
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- W2751293135 doi "https://doi.org/10.1007/978-3-319-62521-8_44" @default.
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