15 August 2007 A new approach for segmentation of forest images based on the color and texture
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Abstract
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.
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Qinghong Sheng, Jianqing Zhang, Hui Xiao, Lihua Xu, "A new approach for segmentation of forest images based on the color and texture", Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 67520I (15 August 2007); doi: 10.1117/12.760430; https://doi.org/10.1117/12.760430
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