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Digital image processing method of video extensometer with automatic tracking laser marker

A video extensometer and laser marking technology, applied in image data processing, image enhancement, image analysis, etc., can solve the problem of inability to meet the real-time requirements of video extensometer, and achieve the effect of strong anti-light interference ability and high recognition accuracy.

Inactive Publication Date: 2013-12-11
ZHEJIANG SCI-TECH UNIV
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Problems solved by technology

However, these methods have their own shortcomings and cannot meet the real-time requirements of video extensometers.

Method used

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  • Digital image processing method of video extensometer with automatic tracking laser marker
  • Digital image processing method of video extensometer with automatic tracking laser marker
  • Digital image processing method of video extensometer with automatic tracking laser marker

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Embodiment Construction

[0021] The present invention will be further described below in conjunction with drawings and embodiments.

[0022] A material deformation measurement device based on laser marking automatic tracking such as figure 2 As shown (see invention patent ZL201110197130.5), this device is also called video extensometer in the present invention, which mainly includes laser scanning automatic tracking control system (it consists of laser 1, reticle 2, pentaprism 3, servo motor Composed of driver 4), computer 5, image acquisition card 6, CCD7, laser marker 8, sample marker 9 and sample 10 and other parts. When the system is working, the CCD collects the image of the tensile sample in real time, and transmits it to the computer through the image acquisition card. The digital image processing algorithm is preprocessed, and the mark is extracted to calculate the displacement difference between the two marks. The sample mark completes the material deformation measurement.

[0023] The flo...

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Abstract

The invention discloses a digital image processing method of a video extensometer with an automatic tracking laser marker. The method includes the steps that a CCD is used for obtaining a sample image, the sample image is input to a computer through an image capture card, and normalization processing is conducted on the sample image to obtain the M*N sample image; the pixel value of each pixel in the sample image is corrected by the way of using a linear brightness adjustment algorithm based on image statistical information; defogging is carried out on the sample image through a selection of a Top-Hat conversion contrast ratio stretching method; an RGB color space is converted into a YCbCr color space, and the laser marker is extracted by the adoption of a self-adaptation Cr chromaticity threshold segmentation algorithm; then, the position of the laser marker is extracted to obtain an interesting image region only including a sample marker and the laser marker, and the sample marker is extracted by the way of using an image brightness gradient in the region; a technological base is provided for real-time precision tracking of the laser marker to the sample marker and material deformation solving. The digital image processing method of the video extensometer with the automatic tracking laser marker has strong robustness to changes in light intensity, environmental anti-jamming capability is strong, and the two markers are high in recognition precision.

Description

technical field [0001] The invention relates to a digital image processing method, in particular to a digital image processing method of a laser marking automatic tracking video extensometer. Background technique [0002] Video extensometers are the primary tool for material deformation measurement. Before measurement, mark is made on the sample, and then the image of the sample collected by CCD is preprocessed and the mark is extracted through digital image processing to obtain the real-time deformation of the sample. The quality of marker extraction algorithm is the key technology to determine the measurement accuracy of video extensometer. [0003] At present, the commonly used image target feature extraction algorithms are mainly based on edge detection and template matching. The edge detection algorithm generally uses methods such as gray threshold segmentation and step-by-step method to extract the pixel-level rough edges of the marked area, and then uses methods suc...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T7/00
Inventor 田秋红陈本永严利平谢森栋
Owner ZHEJIANG SCI-TECH UNIV
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