2D Gabor Functions and FCMI Algorithm for Flaws Detection in Ultrasonic Images
2D Gabor Functions and FCMI Algorithm for Flaws Detection in Ultrasonic Images
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DOI：
10.5281/zenodo.1062172
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发表时间：
2007-09
期刊：
影响因子：
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通讯作者：
Kechida Ahmed;Drai Redouane;K. Mohamed
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文献类型：
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作者：
Kechida Ahmed;Drai Redouane;K. Mohamed
本文提出了一种基于纹理特征的T.O.F.D（TimeOfFlightDiffraction）型超声图像缺陷检测新方法。纹理是识别图像中图案的最重要的特征之一。本文描述了基于二维Gabor函数的纹理特征，即，高斯形状的带通滤波器，具有径向空间频率范围和多个方向的二元处理，这代表了需要在空间和频率域同时测量的任务的适当选择。最相关的功能被用作模糊c均值聚类分类器的输入数据。存在的类只有两个：“缺陷”或“无缺陷”。所提出的方法进行了测试，在实验室和工业现场实现的T.O.F.D图像。
In this paper we present a new approach to detecting a flaw in T.O.F.D (Time Of Flight Diffraction) type ultrasonic image based on texture features. Texture is one of the most important features used in recognizing patterns in an image. The paper describes texture features based on 2D Gabor functions, i.e., Gaussian shaped band-pass filters, with dyadic treatment of the radial spatial frequency range and multiple orientations, which represent an appropriate choice for tasks requiring simultaneous measurement in both space and frequency domains. The most relevant features are used as input data on a Fuzzy c-mean clustering classifier. The classes that exist are only two: 'defects' or 'no defects'. The proposed approach is tested on the T.O.F.D image achieved at the laboratory and on the industrial field.