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

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...

AI Technical Summary

Problems solved by technology

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

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