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Application of image segmentation of aero-engine based on genetic algorithm and region growth

机译:基于遗传算法和区域增长的航空发动机图像分割应用

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Endoscope detection segmentation is important for the detection of numerous faults and plays an important role in the automatic endoscope detecting systems. In this paper, we propose a new image segmentation algorithm introducing threshold selecting based on the genetic algorithm into the region growth. Genetic Algorithm is powerful in optimizing the feature vector through declining useless features and finding optimal ones. The GA is used to choose an optimal threshold to complete the seed generation. Gray-level and texture are used to merge regions with similar characteristics. Experimental results show that the proposed segmentation effect of the method is ideal, and the efficiency is improved.
机译:内窥镜检测分段对于检测大量故障很重要,并且在自动内窥镜检测系统中起着重要作用。在本文中,我们提出了一种新的图像分割算法,该算法将基于遗传算法的阈值选择引入到区域增长中。遗传算法通过减少无用特征并找到最佳特征来优化特征向量。 GA用于选择最佳阈值以完成种子生成。灰度和纹理用于合并具有相似特征的区域。实验结果表明,该方法分割效果理想,提高了效率。

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