An infrared thermal image processing method based on spatial correlation

Abstract

The invention discloses an infrared thermal image processing method based on spatial correlation. Firstly, the video stream data in the heating stage is collected online in real time, then the edge information is extracted, the correlation between two adjacent frames is analyzed, the correlation coefficient is calculated, and the The time-varying correlation coefficient curve reflects the difference in the thermal response state of the test piece after multiple defects are coupled during the heating process. Finally, several suitable thermal images are selected according to the preset value and fused for subsequent defect detection. detection.

Description

technical field [0001] The invention belongs to the technical field of infrared thermal image processing, and more specifically relates to a spatial correlation-based infrared thermal image processing method. Background technique [0002] At present, infrared thermal imaging non-destructive testing technology has become an important branch of non-destructive testing technology. In the non-destructive testing technology of infrared thermal imaging, the research on defect extraction and image enhancement has obtained many achievements. Infrared thermal imaging detection technology can have many detection methods. The excitation source of pulse thermal imaging non-destructive testing is active, and the commonly used excitation sources include hot water, thermal air flow, flash lamp, ultrasonic wave, microwave, laser and electric current. Different heating methods produce different forms of heat. For the current excitation heating method, the heating range is wide, the heat c...

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Problems solved by technology

[0008] From the above scientific research results, although the extraction of defect information has a good effect, a large number of current research methods still collect all thermal image sequences and then process them, or collect data in the heating stage or cooling stage separately. In this way, not only the amount of calculation is too large, but also there is information redundancy, which makes the detection efficiency not high

At the same time, the defect detection of the above research is still based on a single defect or the coupling effect of multiple defects can be ignored, and does not consider the simultaneous existence and mutual influence of multiple defects, and there is a lack of corresponding research on multi-defect detection

Although methods such as Fourier transform, principal component analysis, and independent component analysis are effective for single defect detection, their effectiveness needs to be verified when multiple defects exist and thermal fields are coupled with each other.

At the same time, the above numerical methods do not consider the physical meaning of the eddy current pulse thermal imaging data, and the mining of the physical information of the data itself is extremely limited

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