Abstract
The detection accuracy of the light stripe centers is an important factor based on the structured light vision measurement, and the quality of the light stripe images is a prerequisite for accurately detecting the light stripe centers; this paper separately proposes image enhancement methods for linear and arc light stripe images. For linear light stripes, the image with better quality is captured and the gray-scale distribution of the normal section corresponding to the light stripe centers is used as a template for light stripe images with poor quality. The poor quality light stripe images are finally optimized by linear interpolation. For arc-shaped light stripes, this paper proposes a positioning method for light stripe centers on arc, and then the gray-scale distribution of the normal cross-section of corresponding center which is on a good quality light stripe image is used as templates to improve the poor quality light quality stripe images. In order to verify the effectiveness of the light stripe image enhancement algorithms, this paper respectively presents verification methods to linear light stripe and arc light stripe. Finally, the quality of the light stripe images could be improved by image enhancement algorithms through experiments.
Highlights
The measurement methods based on machine vision have been in-depth research and rapid development in the three-dimensional measurement of mechanical parts [1–3]
In order to ensure the consistency of the experiment, the light stripe centers are According to Table 3, the uniformity of the light stripe centers after enhancement is better than the light stripe centers before processing
The light stripe centers corresponding to the image before and after optimization are detected by the Steger algorithm, and the light stripe image enhancement algorithm is verified by the evaluation method proposed in this paper
Summary
The measurement methods based on machine vision have been in-depth research and rapid development in the three-dimensional measurement of mechanical parts [1–3]. Due to its advantages of large range, good robustness, and high precision, the measurement method based on the structured light vision has been widely developed in the parts size measurement [4–7]. According to the different characteristics of structured light sources, they can be divided into different types. The paper mainly studies the widely used line structured light vision. The structured light measurement technology can be divided into the following three parts: vision system calibration [8], light stripe center detection [9], and measurement model establishment. The detection precision of the structured light stripe centers is an important factor affecting the measurement accuracy of the vision system. The detection accuracy of the light stripe centers is affected by the detection algorithm, and the quality of the light stripe images is a prerequisite for
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