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Comment on image segmentation algorithm under the background of information age

机译:信息时代背景下的图像分割算法评述

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At present, various kinds of electronic imaging equipment have emerged endlessly, and the means of image processing are also continuously updated. As a basic technological means of image processing, image segmentation impacts on the quality of image processing. Image segmentation algorithm has many types, people measure between the qualities of image segmentation and the time required to process, and then pick out the best. This paper has discussed three image segmentation algorithms in detail, those are image segmentation algorithm based on calculus of variations, image segmentation algorithm based on clustering methodology, and image segmentation algorithm based on genetic algorithm. Image segmentation steps of these three types are respectively represented and the effects of those are shown. Meanwhile, the goal programming theory knowledge can be used to compare among the OTSU image segmentation method, the basic genetic algorithm and IGA algorithm. The result of comparison shows that IGA algorithm is the most effective one, which is consistent with the experimental results.
机译:当前,各种电子成像设备层出不穷,并且图像处理手段也不断更新。作为图像处理的基本技术手段,图像分割会影响图像处理的质量。图像分割算法有多种类型,人们在图像分割的质量和处理所需的时间之间进行衡量,然后挑选出最佳的算法。本文详细讨论了三种图像分割算法,分别是基于变化演算的图像分割算法,基于聚类方法的图像分割算法和基于遗传算法的图像分割算法。分别表示了这三种类型的图像分割步骤,并显示了它们的效果。同时,目标规划理论知识可以用来比较OTSU图像分割方法,基本遗传算法和IGA算法。比较结果表明,IGA算法是最有效的,与实验结果吻合。

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