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边缘生长    
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  edge growing
    The edge of target is incomplete because of effecting by speed of vehicles,freight flow,noise and so on. Mending the edge of target with edge growing in order to improve the accuracy of moving vehicles detection and smooth the edge.
    受车速,车流量,噪声等影响,得到的是不完整的目标边缘,依靠边缘生长对目标进行修补,以提高运动车辆检测的准确性,保证边缘的连续性.
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  edge growing
    The edge of target is incomplete because of effecting by speed of vehicles,freight flow,noise and so on. Mending the edge of target with edge growing in order to improve the accuracy of moving vehicles detection and smooth the edge.
    受车速,车流量,噪声等影响,得到的是不完整的目标边缘,依靠边缘生长对目标进行修补,以提高运动车辆检测的准确性,保证边缘的连续性.
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  edge growing
It can be seen that the proposed multi-scale edge growing algorithm produces edges with better connectivity and better saliency.
      
In the example in Figure 2, the main edge growing is associated with the DEM-derived edges.
      
The edge growing algorithm therefore suffers less from the topological damage resulting from nonmaximum suppression.
      
  edge growing
It can be seen that the proposed multi-scale edge growing algorithm produces edges with better connectivity and better saliency.
      
In the example in Figure 2, the main edge growing is associated with the DEM-derived edges.
      
The edge growing algorithm therefore suffers less from the topological damage resulting from nonmaximum suppression.
      
  edge growth
Annual variation of scale edge growth rate (α) indicates that the annulus forms once a year, mainly in April-June.
      
Deformed sea urchins showed low calcification rates and aberrant plate calcification gradients, as well as irregular sutural calcification patterns, characterized by very high vertical vs horizontal plate-edge growth ratios (v/h).
      
Metamorphosis in the Chilean oyster Ostrea chilensis was complete 36?h after release of the larvae, when 100% of the individuals showed edge growth of the dissoconch.
      
The first scales deposited commence assembly at the cell posterior and the wall develops anteriorly by edge growth.
      
The criteria for rough edge growth and survival after 72 h incubation in low-serum differentiation media were by subjective observation.
      
  其他


According to the first geographic law of Tobler and the Marr's machine vision theory,an algorithm to segmenting multi-spectral remote sensing imageries has been put forward based on the edge information extracted from them.This algorithm consists of four steps listed below:(1) Detecting edge information in each band of remote sensing imageries using a improved Canny method;(2) Integrating edge information in each band of remote sensing imageries into a binary image by methods such as overlay technique in GIS...

According to the first geographic law of Tobler and the Marr's machine vision theory,an algorithm to segmenting multi-spectral remote sensing imageries has been put forward based on the edge information extracted from them.This algorithm consists of four steps listed below:(1) Detecting edge information in each band of remote sensing imageries using a improved Canny method;(2) Integrating edge information in each band of remote sensing imageries into a binary image by methods such as overlay technique in GIS technology,and then thinning edges in the binary image by techniques of mathematical morphology using a rectangle probe;(3) conjoining disconnected edges according to the characteristics of processing edge such as length,direction and so on,to close each region;(4) at last,labeling region and remove abundant edges that do not compose region.Then,the multi-spectral remote sensing imageries of Quickbird covering the Kumamoto city,Japan,have been taken as a case study for this algorithm,and the result has been compared with other segmentation algorithms such as Multi-Threshold Gray Slice Approach(MTGSA),Iterative Self-Organized Data Analysis Technology Algorithm(ISODATA) image segmentation algorithm,Watershed Segmentation Algorithm(WSA),Fractal Net Evolution Approach(FNEA) and so on.Based on the comparative analysis,conclusions could be drawn out that(1) In term of utilizing brightness information of each band,the scope that the algorithm proposed in the paper is the most comprehensive one,and MTGSA and WSA can only use single band of multi-spectral remote sensing image;(2) The result of this algorithm could be the most satisfied,as it detects edge information of each spectral band respectively,and then integrates as well as connects them together,maximally digging out the detailed features in remote sensing imageries;(3) In the aspect of computational duration,this algorithm is relatively a bit faster than others under the same environment.As the same as the other three approaches,the algorithm proposed in the paper has also confronted the common difficulty of how to confirm the coefficient in the image segmentation procedure.

从M arr视觉计算理论和Tob ler地学第一定律出发,提出了基于边缘的多光谱遥感图像分割方法。在基于边缘的多光谱遥感图像分割方法中,由边缘检测、边缘综合、边缘生长、区域标号等环节组成。该遥感图像分割方法在可视化开发平台Delph i中予以编程实现。将之应用于日本熊本市(Kum amoto)的Qu ickb ird多光谱遥感图像中,并与多种遥感分割算法进行了比较:(1)从多光谱遥感图像各波段亮度信息利用的程度上看,提出的遥感图像分割方法能充分利用多波段亮度信息;(2)从遥感图像分割结果上看,由于分别对不同的波段进行边缘检测,并在此基础上进行边缘综合、边缘生长,遥感图像中的细节特征得到了充分体现,遥感图像分割效果更理想;(3)从计算复杂度和计算效率上看,基于边缘的多光谱遥感图像分割法较其他分割方法有一定的优势。

This paper employs a multichannel edge detecting approach to traffic color video image in RGB space,an adaptive background model is built on the frames iteration of fused edge information and the moving vehicles are based on the background model subtraction.The edge of target is incomplete because of effecting by speed of vehicles,freight flow,noise and so on.Mending the edge of target with edge growing in order to improve the accuracy of moving vehicles detection and smooth the edge.The experimental results...

This paper employs a multichannel edge detecting approach to traffic color video image in RGB space,an adaptive background model is built on the frames iteration of fused edge information and the moving vehicles are based on the background model subtraction.The edge of target is incomplete because of effecting by speed of vehicles,freight flow,noise and so on.Mending the edge of target with edge growing in order to improve the accuracy of moving vehicles detection and smooth the edge.The experimental results show that the method needs little calculation,and can satisfy the requirement of the real-time system and detect moving vehicles effectively.

在RGB空间中对彩色交通视频图像进行多通道边缘检测,利用融合的边缘信息进行多帧迭加建立自适应背景模型,通过背景模型抽取运动车辆.受车速,车流量,噪声等影响,得到的是不完整的目标边缘,依靠边缘生长对目标进行修补,以提高运动车辆检测的准确性,保证边缘的连续性.实验结果表明,该方法计算量小,能够满足实时系统的要求,可有效地检测运动车辆.

 
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