Applicability of Motion Estimation Algorithms for an Automatic Detection of Spiral Grain in CT Cross-Section Images of Logs

机译：运动估计算法在原木CT截面图像中自动检测螺旋纹的适用性

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摘要

Techniques for an automatic detection of spiral grain in cross-section CT images of logs are proposed and evaluated on sets of natural and artificial cross-section images. Explicit analysis of global rotation, block matching, and optical flow techniques are compared. Experimental results seem to indicate that spiral grain in fact cannot be modeled by a circular motion of luminance values in gray scale images.

机译：提出了一种自动检测原木横截面CT图像中螺旋纹的技术，并在自然和人工横截面图像集上进行了评估。比较了全局旋转，块匹配和光流技术的显式分析。实验结果似乎表明，实际上无法通过灰度图像中亮度值的圆周运动来建模螺旋纹。

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来源
《International Conference on Computer Analysis of Images and Patterns(CAIP 2007); 20070827-29; Vienna(AT)》|2007年|P.36-44|共9页
会议地点 Vienna(AT)
作者
Karl Entacher; Christian Lcnz; Martin Seidel; Andreas Uhl; Rudolf Weiglmaier;
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作者单位

Salzburg University of Applied Sciences, Austria;

Department of Computer Sciences, Salzburg University, Austria;

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原文格式 PDF
正文语种 eng
中图分类信息处理（信息加工）;
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Applicability of Motion Estimation Algorithms for an Automatic Detection of Spiral Grain in CT Cross-Section Images of Logs

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