A Background Suppression Algorithm for Detection of Steel Coil End Face Defects
A technology of background suppression and defect detection, applied in computing, image analysis, image enhancement, etc., can solve problems such as no solution, inapplicable defect detection, and inability to process visible light images, so as to improve the effect and suppress the problem of highlighting defect parts Effect
Active Publication Date: 2020-08-07
重庆赛迪奇智人工智能科技有限公司
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Problems solved by technology
One of the directions is background suppression for infrared images, but it cannot handle visible light images
The second direction is for moving targets in a fixed background, and the background can be filtered out by using the frame difference method, etc. However, this method is obviously not suitable for defect detection
However, there is no general solution for complex and variable visible light image backgrounds
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[0033] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.
[0034] The present invention provides a background suppression algorithm aimed at the detection of steel coil end surface defects, such as Figure 1-5 shown, including the following steps:
[0035] Step S1, input a local grayscale image of the end face of the steel coil, and use the local grayscale Figure II Dimensional array f(x,y) representation, local grayscale Figure II Dimensional array f(x,y) is M rows and N columns; for local grayscale Figure II The two-dimensional array f(x,y) performs two-dimensional discrete time-fre...
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The invention provides a background suppression algorithm for steel coil end face defect detection, which comprises the following steps of: inputting a local grey-scale map of a steel coil end face, and carrying out two-dimensional discrete time-frequency conversion on a local grey-scale map two-dimensional array f (x, y); equally dividing The spectrogram two-dimensional array F (u, v) into four quadrants; translating the diagonal quadrant of the two-dimensional array F (u, v) matrix of the spectrogram for position exchange to obtain a translated spectrogram F _ shift (u, v); converting the translation spectrogram into an amplitude spectrogram, and splitting the amplitude spectrogram two-dimensional array M (u, v) into a low-frequency component spectrogram two-dimensional array M _ low (u,v) and other component spectrogram two-dimensional arrays M _ else (u, v); Setting pixel points corresponding to the background frequency spectrum direction in the translation frequency spectrum two-dimensional array F _ shift (u, v) to be zero so as to obtain a new frequency spectrum two-dimensional array F _ field (u, v); And carrying out two-dimensional discrete time-frequency inverse transformation on the two-dimensional array F _ field (u, v) of the new spectrogram to obtain a local grayscale image f '(x, y) after background suppression. The method can be used for carrying out backgroundsuppression on the end surface of the steel coil, and compared with the existing filtering algorithm, the effect is greatly improved.
Description
technical field [0001] The invention relates to the technical field of machine vision, in particular to a background suppression algorithm for detection of steel coil end surface defects. Background technique [0002] In the field of machine vision, there are already many defect detection applications, but the background of most defect detection applications is relatively simple, with less texture and little change, and the interference caused by the background is relatively small. For application scenarios with complex backgrounds, it is necessary to perform background suppression first, so that better results can be obtained later. [0003] The existing background suppression algorithms are all for specific scenes. One direction is background suppression for infrared images, but it cannot handle visible light images. The second direction is for moving objects in a fixed background, and the background can be filtered out by using the frame difference method, etc. However,...
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IPC IPC(8): G06T7/00G06T5/20G06T3/00
Inventor 张发恩蒋晓路黄家水
Owner 重庆赛迪奇智人工智能科技有限公司