Multilevel edge detection using quantum and classical genetic algorithms: A comparative study
نویسندگان
چکیده
In this work, we develop a multilevel edge detection method based on the Kapur and Tsallis entropies. The multilevel thresholding approach gives rise to an NP-hard optimization problem. We have used the Classical Genetic Algorithm (CGA) and the Quantum Genetic Algorithm (QGA) to solve this problem. The performance of the QGA has been tested on ten sample images and it is shown that the QGA outperforms significantly the CGA on a sample of real-world images. Moreover, it was found that the Kapur entropy is leads to a slightly better image segmentation quality than the Tsallis one.
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