مشخصات مقاله | |
ترجمه عنوان مقاله | کاربردهای پردازش تصویر در رباتیک و ابزار دقیق |
عنوان انگلیسی مقاله | Applications of image processing in robotics and instrumentation |
انتشار | مقاله سال 2019 |
تعداد صفحات مقاله انگلیسی | 28 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس نمیباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
6.032 در سال 2018 |
شاخص H_index | 134 در سال 2019 |
شاخص SJR | 1.821 در سال 2018 |
شناسه ISSN | 0888-3270 |
شاخص Quartile (چارک) | Q1 در سال 2018 |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | کامپیوتر – مهندسی برق – رباتیک |
گرایش های مرتبط | مهندسی نرم افزار، ابزار دقیق، مهندسی الگوریتم ها و محاسبات |
نوع ارائه مقاله |
ژورنال |
مجله | سیستمهای مکانیکی و پردازش سیگنال – Mechanical Systems And Signal Processing |
دانشگاه | School of Mechanical Engineering, University of Campinas, R. Mendeleyev 200, 13083860 Campinas, Brazil |
کلمات کلیدی | پردازش تصویر، رباتیک، ابزار دقیق، بررسی ابعادی میل لنگ، هم ترازی چرخش، سنجش بصری |
کلمات کلیدی انگلیسی | Image processing، Robotics، Instrumentation، Crankshaft dimensional verification، Wheel alignment، Visual odometry |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.ymssp.2019.01.015 |
کد محصول | E12706 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract
1- Introduction 2- Camera, image and color models 3- Image processing techniques 4- Application 1: Wheel rim detection 5- Application 2: Automatic 3-D crankshaft verification system 6- Application 3: Wheel alignment measuring system 7- Application 4: Stereo visual odometry for mobile robotics 8- Conclusion References |
بخشی از متن مقاله: |
Abstract Modern applications of industrial automation and robotics are increasingly relying on image processing techniques. This paper shows ways in which image processing can be applied to solve actual problems in robotics and instrumentation. The paper starts by presenting the fundamentals of camera models, digital acquisition of images and selected processing techniques, followed by examples of applications of such knowledge. Four examples of image processing applications are shown: rim detection in automotive wheel images, dimensional verification of crankshafts, measurement of wheel alignment angles of a car and a stereo visual odometry algorithm for mobile robotics. The examples not only illustrate the uses of different image processing techniques, but may also inspire the development of new robotic and industrial automation products. Introduction The engineering community is experiencing a dramatic growth in application of image processing as a tool to perform non-intrusive precision measurement, autonomous robot navigation or reliable verification of industrial automation processes. Image acquisition and processing techniques are familiar to physics, computer, electrical and mechanical engineering sciences for a relatively long time. Specialized literature on this field is usually dedicated to specific aspects such as the geometry of camera projections and computer vision [1–5], image acquisition and processing [6], or either the scientific and industrial applications of image processing and analysis [7]. This paper is both a review and a tutorial of applied image processing in industrial automation, aimed at researchers, postgraduate students and engineers. Digital images can be associated with geometric properties of objects, such as shapes and dimensions, which enables a myriad of applications and developments. In order to exploit such possibilities, the paper provides insight into some of the key techniques associated with image acquisition, processing and analysis. Theoretical aspects on the geometry of perspective projection, camera calibration, epipolar geometry and stereo image correspondence are further elaborated with regards to technical details. Such a mathematical framework is the core for the use of cameras as measuring devices in photogrammetry. Four applications of image processing are shown through examples in actual robotics and instrumentation scenarios: rim detection in automotive wheel images; dimensional verification of crankshafts; measurement of the wheel alignment angles of a car, and a stereo visual odometry algorithm for mobile robotics. The examples are innovative concepts that can inspire a wider range of image-related applications. Each example considers four aspects: (1) a motivation; (2) an explicit description of the system setup and calibration; (3) mathematical rationale and references to first principles that explicit the assumptions behind each application; (4) empirical results and discussion. |