文件名称:CV
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针对传统Chan-Vese(CV)模型对公路路面破损图像分割的局限性,将图像梯度信息引入CV 模型,利用路面破损区域纹理与背景的
不同,对图像进行分割。引入梯度阈值,将图像的灰度信息和纹理信息相结合,从而使分割方法更具灵活性-Distress image segmentation on the road surface limitations for traditional Chan-Vese (CV) model, the introduction of image gradient information CV model, the use of the road surface texture and background of the damaged area of the different image segmentation. To introduce gradient threshold, combining image intensity and texture information, so that the segmentation method more flexibility
不同,对图像进行分割。引入梯度阈值,将图像的灰度信息和纹理信息相结合,从而使分割方法更具灵活性-Distress image segmentation on the road surface limitations for traditional Chan-Vese (CV) model, the introduction of image gradient information CV model, the use of the road surface texture and background of the damaged area of the different image segmentation. To introduce gradient threshold, combining image intensity and texture information, so that the segmentation method more flexibility
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改进的公路破损路面图像分割CV模型.pdf
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