2D Gabor Functions and FCMI Algorithm for Flaws Detection in Ultrasonic Images

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.

Authors:

• Kechida Ahmed
• Drai Redouane
• Khelil Mohamed

Keywords:

• 2D Gabor Functions
• flaw detection
• fuzzy c-mean clustering
• non destructive testing
• texture analysis
• T.O.F.D Image (Time of Flight Diffraction).

References:

[1] S W. Lawson and G.A. Parker "Automatic detection of defects in
industrial ultrasound images using a neural network", Proc. of Int.
Symposium on Lasers, Optics, and Vision for Productivity in
Manufacturing I (Vision Systems: Applications), June 1996, Proc. of
SPIE vol. 2786, pp. 37-47, 1996.
[2] Kumar, A, Pang, G K H, 2002: Defect Detection in Textured Materials
Using Gabor Filters. IEEE Transactions on Industry Applications,
38(2):425-440.
[3] M.Friedman, A.Kandel, "introduction to the pattern recognition,
statistical, structural, neural and fuzzy logic approaches" Ed imperial
college Press 1999.
[4] SILK, M.G., "The use of diffraction based time-of-flight measurements
to locate and size defects", Brit. J. of NDT, vol. 26, 1984, pp 208-213.
[5] SILK, M.G., "The rapid analysis of TOFD data incorporating the
provisions of standards", in Proc. of 6thEuropean Conf on NDT, 1994,
pp 25-29.