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line-segment extraction
相关语句
  线段提取
     An Algorithm of Line-segment Extraction and Thinning for Character Images
     一种字符图像线段提取及细化算法
短句来源
  相似匹配句对
     On-line
     行业在线
短句来源
     On line
     行业在线
短句来源
     GLOBAL ON-LINE
     环球在线
短句来源
     THE MULTIWAVELETS ON THE LINE
     直线上的多小波
短句来源
     not by line segment.
     肌肉拉力线应用射线来标示;
短句来源
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As part of middle level processing in computer vision, line segments extraction is a bridge between low level processing and high level reasoning and high level computations. Automatically extraction of line segments in a complex scene is very difficult. A new technique that extracts line segments from directed edge images by labeling and growing was proposed. This technique labels on edge pixels of similar directions, and seeks a line segment candidate for the current edge pixel in its...

As part of middle level processing in computer vision, line segments extraction is a bridge between low level processing and high level reasoning and high level computations. Automatically extraction of line segments in a complex scene is very difficult. A new technique that extracts line segments from directed edge images by labeling and growing was proposed. This technique labels on edge pixels of similar directions, and seeks a line segment candidate for the current edge pixel in its directed neighborhood. The experimental results show the validity of this technique in the cases of complex scenes. Some defects of this technique and further work directions were also presented.

作为计算机视觉的中层处理部分,线段提取具有重要意义,它是底层处理到高层推理和高层计算的桥梁.在复杂的背景图像中自动提取出线段是可能的,却又是十分困难的.为此,提出一个基于有向边缘图像利用标记生长提取线段的新方法,它以同类方向边缘像素为标记对象,在当前像素的有向邻域中搜索相应的线段.实验结果表明,该方法在复杂图像中的有效性

The paper presents a general paradigm of semiautomatic building extraction from aerial stereo image pair.In the semiautomatic extraction system,the building model is defined by selected roof type input through human_machine interface and input points of rough position of the building by operator.With the geometrical constraints of the model,low_level and mid_level processing including edge detection,straight line segments extraction and line segments grouping are to establish the initial geometrical...

The paper presents a general paradigm of semiautomatic building extraction from aerial stereo image pair.In the semiautomatic extraction system,the building model is defined by selected roof type input through human_machine interface and input points of rough position of the building by operator.With the geometrical constraints of the model,low_level and mid_level processing including edge detection,straight line segments extraction and line segments grouping are to establish the initial geometrical model of the roof_top.However,the initial geometrical model is not so accurate in geometry.To attain accurate results,straight_line extraction and positioning by least squares matching with object_space based geometrical constraints rectifies the initial geometrical model.The adjustment model integrates the straight edge pattern and 3D constraints together and is a well_studied optimal method.The edge model is based on strict zero_crossing definition,and the strict geometrical constraints of the corners of the extracted building as 'knowledge' that is clearly described by the adjustment model are fused with image feature,such as edge and straight line.The model uses all of the information and constraints of the building borders to attain an optimal result,so this is a model driven strategy that matches the roof model with the image pair depending on the criteria of least squares.In principle,the method does not need feature detection,so there are no threshold problemes.After gaining proper initial values,the adjustment model can flexibly process extraction of kinds of roof types by changing or assembling the geometrical constraints in object_space. On the other hand,the paper also discusses the scheme of practical system of semiautomatic extraction.To build a practical semiautomatic extraction system,correctness,accuracy,robustness,speed and interactivity,all these factors should be taken into account.In the paper,a robust algorithm of extracting main direction of the house is addressed.By detecting edge,tracing the edge chain vectors and extracting straight_line segments,a Weighted Histogram of Angles (WHoA) is generated by the angles of extracted line segments.With the histogram,the main direction of the building can be easily detected by searching the max value of the histogram.Histogram method is a statistical manner like Hough transformation; it can effectively remove the influences of gaps between collinear segments and racket segments.The experiments show that that main direction and outer border detection by the WHoA method is robust.The line segments extraction and confirming the main direction of the house could save the operator's input action and offer good initial values of the corners for the consequent adjustment evaluation.

提出了一种从数字航空立体像对半自动提取建筑物的方法。操作员通过人机界面选择房屋的种类并输入初始位置 ,然后经过边缘检测、直线段提取和据此房屋几何模型的线段自动编组等处理得到各房屋角点的初始位置。最后 ,为了获得房屋的精确定位和符合物方严格几何约束的结果 ,基于物方空间几何约束的最小二乘匹配平差模型用于求取房屋直线边缘和物方几何模型的最优匹配。试验表明 ,该方法能提高建筑物的提取精度并可为半自动建筑物提取提供一个灵活的框架

Perceptual organization is a powerful tool for automatic detection objects. In this paper, a perceptual organization approach based on Bayesian Networks is proposed, and used as a method of detection 3-D man made structure objects, such as buildings et al., from urban aerial image. Objects are detected by means of hypotheses verification, and the approach is divided into four steps: edges and lines segments extraction, parallelograms creation, hypotheses creation, and hypotheses verification. Two Bayesian...

Perceptual organization is a powerful tool for automatic detection objects. In this paper, a perceptual organization approach based on Bayesian Networks is proposed, and used as a method of detection 3-D man made structure objects, such as buildings et al., from urban aerial image. Objects are detected by means of hypotheses verification, and the approach is divided into four steps: edges and lines segments extraction, parallelograms creation, hypotheses creation, and hypotheses verification. Two Bayesian Networks are designed for information integration in the process of hypotheses creation, and hypotheses verification respectively. With the learning function from Bayesian Networks, the approach is provided with self-adaptation to some extent. The validity of this approach is indicated by experiment.

感知组织是自动检测目标的有力工具。文章提出一个基于Bayes网络的感知组织算法,用于检测城市航空影象中房屋等三维人造结构体。算法使用假设检验的方法检测目标,由提取边缘及线段、生成平行四边形、生成假设、检验假设四个步骤组成。文中设计了两个Bayes网络分别作为假设生成和检验中的信息融合工具。Bayes网络的学习能力,使算法具有一定的自适应性。实验结果表明了算法的有效性。

 
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