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A new approach for segmentation of forest images based on the color and texture

机译:基于颜色和纹理的森林图像分割的一种新方法

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To solve the problem of interposition between trees or trees and between trees and ground in forest images which would bring on error-matching and be unable to construct a full 3D-network, a new approach for segmentation of forest images was proposed. The proposed color divergence was defined over the index class map by quantized image, which was a good indicator of whether that area was in region center or near region boundaries. Using this measure, image texture was analyzed by multi-resolution. Then the initial over-segmented regions were merged according to Laws texture energy measure. Experimental demonstrated that the segmentation results of forest images on the proposed approach hold favorable consistency in terms of human perception. The classification accuracy was 80%. The recognized trees and ground can offer dependable data for image matching and 3D modeling.
机译:为了解决树木或树木之间的插入问题以及在森林图像中的树木和地面之间,这将引入错误匹配并且无法构建完整的3D网络,提出了一种新的森林图像分割方法。通过量化图像在索引类地图上定义了所提出的颜色分歧,这是该区域是否在区域中心或近区域边界中的良好指标。使用该措施,通过多分辨率分析图像纹理。然后根据法律纹理能量措施合并初始过分分段区域。实验证明,森林形象的分割结果在拟议的方法中对人类感知方面具有良好的一致性。分类准确度为80%。公认的树木和地面可以为图像匹配和3D建模提供可靠的数据。

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