A system for detection of internal log defects by computer analysis of axial CT images

S. Bhandarkar, T. D. Faust, Mengjin Tang
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引用次数: 26

Abstract

The paper presents a system for detection of some important internal log defects via analysis of axial CT images. Two major procedures are used. The first is the segmentation of a single computer tomography (CT) image slice which extracts defect-like regions from the image slice, the second is correlation analysis of the defect-like regions across CT image slices. The segmentation algorithm for a single CT image is basically a complex form of multiple thresholding that exploits both the prior knowledge of wood structure and gray value characteristics of the image. The defect-like region extraction algorithm first locates the pith, groups the pixels in the segmented image on the basis of their connectivity and classifies each region as either a defect-like region or a defect-free region using shape, orientation and morphological features. Each defect-like region is classified as a defect or non-defect via correlation analysis across corresponding defect-like regions in neighboring CT image slices.
一种利用计算机分析轴向CT图像检测原木内部缺陷的系统
本文介绍了一种利用轴向CT图像分析检测原木内部重要缺陷的系统。主要有两个步骤。首先是对单个CT图像切片进行分割,从图像切片中提取类缺陷区域;其次是对CT图像切片中类缺陷区域进行相关性分析。单幅CT图像的分割算法基本上是一种复杂形式的多重阈值分割,它既利用了木结构的先验知识,又利用了图像的灰度值特征。类缺陷区域提取算法首先定位髓点,根据其连通性对分割图像中的像素进行分组,并根据形状、方向和形态特征将每个区域分类为类缺陷区域或无缺陷区域。通过对相邻CT图像切片中相应缺陷样区域的相关性分析,将每个缺陷样区域划分为缺陷或非缺陷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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