{"title":"环境光干扰下轨道车辆轮纹轮廓的激光条纹分割算法","authors":"","doi":"10.1016/j.optlaseng.2024.108600","DOIUrl":null,"url":null,"abstract":"<div><p>In the measurement of the wheel tread in rail vehicles, line laser vision measurement technology has a good application prospect. However, the intensity and location of the ambient light will constantly change in the actual application scenarios. Traditional laser stripe segmentation algorithms often fail to produce accurate results, leading to decreased measurement precision in wheel tread. To solve the problem, a segmentation algorithm for laser stripes was proposed. Firstly, the SSR algorithm and frame subtraction were utilized to remove the background noise. Then, the OTSU method was used for the preliminary segmentation. After that, smoothing Images and reducing noise were performed with geometric mean filtering and morphological closing. Finally, the segmentation function which was based on the gray scale distribution characteristics of each region of the image was established to achieve the accurate segmentation of laser stripes. Laser stripe segmentation experiments, laser stripe segmentation comparison experiments, and wheel tread geometry extraction experiments were designed and conducted under the ambient light interference. The experimental results show that the segmentation success rate of the proposed algorithm is not <90.625 %. The proposed algorithm has a superior segmentation effect compared to other algorithms. The proposed algorithm can improve the measurement accuracy. For flange height measurement, the mean error decreased from 0.298 mm to 0.161 mm, and the standard deviation decreased from 0.600 to 0.548. For flange width measurement, the mean error remained constant at 0.200 mm, and the standard deviation decreased from 0.681 to 0.536. Under the condition that the ambient light intensity is in the range of 37lux∼1050 lx and the laser power is not <50mW, the proposed algorithm can better realize the adaptive segmentation of laser stripes.</p></div>","PeriodicalId":49719,"journal":{"name":"Optics and Lasers in Engineering","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A laser stripe segmentation algorithm for wheel tread profile of rail vehicles under ambient light interference\",\"authors\":\"\",\"doi\":\"10.1016/j.optlaseng.2024.108600\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In the measurement of the wheel tread in rail vehicles, line laser vision measurement technology has a good application prospect. However, the intensity and location of the ambient light will constantly change in the actual application scenarios. Traditional laser stripe segmentation algorithms often fail to produce accurate results, leading to decreased measurement precision in wheel tread. To solve the problem, a segmentation algorithm for laser stripes was proposed. Firstly, the SSR algorithm and frame subtraction were utilized to remove the background noise. Then, the OTSU method was used for the preliminary segmentation. After that, smoothing Images and reducing noise were performed with geometric mean filtering and morphological closing. Finally, the segmentation function which was based on the gray scale distribution characteristics of each region of the image was established to achieve the accurate segmentation of laser stripes. Laser stripe segmentation experiments, laser stripe segmentation comparison experiments, and wheel tread geometry extraction experiments were designed and conducted under the ambient light interference. The experimental results show that the segmentation success rate of the proposed algorithm is not <90.625 %. The proposed algorithm has a superior segmentation effect compared to other algorithms. The proposed algorithm can improve the measurement accuracy. For flange height measurement, the mean error decreased from 0.298 mm to 0.161 mm, and the standard deviation decreased from 0.600 to 0.548. For flange width measurement, the mean error remained constant at 0.200 mm, and the standard deviation decreased from 0.681 to 0.536. Under the condition that the ambient light intensity is in the range of 37lux∼1050 lx and the laser power is not <50mW, the proposed algorithm can better realize the adaptive segmentation of laser stripes.</p></div>\",\"PeriodicalId\":49719,\"journal\":{\"name\":\"Optics and Lasers in Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Optics and Lasers in Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0143816624005785\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"OPTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optics and Lasers in Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0143816624005785","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OPTICS","Score":null,"Total":0}
A laser stripe segmentation algorithm for wheel tread profile of rail vehicles under ambient light interference
In the measurement of the wheel tread in rail vehicles, line laser vision measurement technology has a good application prospect. However, the intensity and location of the ambient light will constantly change in the actual application scenarios. Traditional laser stripe segmentation algorithms often fail to produce accurate results, leading to decreased measurement precision in wheel tread. To solve the problem, a segmentation algorithm for laser stripes was proposed. Firstly, the SSR algorithm and frame subtraction were utilized to remove the background noise. Then, the OTSU method was used for the preliminary segmentation. After that, smoothing Images and reducing noise were performed with geometric mean filtering and morphological closing. Finally, the segmentation function which was based on the gray scale distribution characteristics of each region of the image was established to achieve the accurate segmentation of laser stripes. Laser stripe segmentation experiments, laser stripe segmentation comparison experiments, and wheel tread geometry extraction experiments were designed and conducted under the ambient light interference. The experimental results show that the segmentation success rate of the proposed algorithm is not <90.625 %. The proposed algorithm has a superior segmentation effect compared to other algorithms. The proposed algorithm can improve the measurement accuracy. For flange height measurement, the mean error decreased from 0.298 mm to 0.161 mm, and the standard deviation decreased from 0.600 to 0.548. For flange width measurement, the mean error remained constant at 0.200 mm, and the standard deviation decreased from 0.681 to 0.536. Under the condition that the ambient light intensity is in the range of 37lux∼1050 lx and the laser power is not <50mW, the proposed algorithm can better realize the adaptive segmentation of laser stripes.
期刊介绍:
Optics and Lasers in Engineering aims at providing an international forum for the interchange of information on the development of optical techniques and laser technology in engineering. Emphasis is placed on contributions targeted at the practical use of methods and devices, the development and enhancement of solutions and new theoretical concepts for experimental methods.
Optics and Lasers in Engineering reflects the main areas in which optical methods are being used and developed for an engineering environment. Manuscripts should offer clear evidence of novelty and significance. Papers focusing on parameter optimization or computational issues are not suitable. Similarly, papers focussed on an application rather than the optical method fall outside the journal''s scope. The scope of the journal is defined to include the following:
-Optical Metrology-
Optical Methods for 3D visualization and virtual engineering-
Optical Techniques for Microsystems-
Imaging, Microscopy and Adaptive Optics-
Computational Imaging-
Laser methods in manufacturing-
Integrated optical and photonic sensors-
Optics and Photonics in Life Science-
Hyperspectral and spectroscopic methods-
Infrared and Terahertz techniques