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A Novel Approach to Image Edge Enhancement Using Artificial Bee Colony Optimization Algorithm for Hybridized Smoothening Filters

机译:一种使用人工蜂菌落优化算法进行杂交平滑滤波器的一种新方法

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In this Modern era, image transmission and processing plays a major role. It would not be possible to retrieve information from satellite and medical images without the help of Image processing techniques. Image edge Enhancement is the art of examining images for identifying objects and judging their significance. The proposed work uses the concept of Artificial Bee Colony Algorithm which proved to be the most powerful unbiased optimization technique for sampling a large solution space. Because of its unbiased stochastic sampling, it was quickly adapted in image processing and thus for image edge enhancement as well. This paper deals with the techniques that help in improvising the quality of the image edges and in solving various complex image processing tasks such as segmentation, feature extraction, classification and image generation. The edge enhancement is done using hybridized smoothening filters by The Artificial Bee Colony optimization algorithm and compared it with the genetic algorithm.
机译:在这种现代化的时代,图像传输和处理起着重要作用。在没有图像处理技术的帮助下,不可能从卫星和医学图像中检索信息。图像边缘增强是检查用于识别对象并判断其重要性的图像的艺术。该拟议的工作使用人造群落算法的概念,该算法被证明是用于采样大型解决方案空间的最强大的无偏的优化技术。由于其无偏偏心的随机取样,它迅速适用于图像处理,从而快速适用于图像边缘增强。本文涉及有助于提高图像边缘的质量和解决诸如分段,特征提取,分类和图像生成的各种复杂图像处理任务的技术。使用人造蜂菌落优化算法使用杂交的平滑滤波器进行边缘增强,并将其与遗传算法进行比较。

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