Abstract
With the development of society, robots gradually replace the human beings. The research of machine vision sensing is particularly important. This paper combines the open-source and the free OpenCV2.4.9 computer vision library, Daheng Imavision, and its development kit and VS2013 to achieve the docking. The format conversion of image data captured by industrial Imavision is successful, which adapts to the direct processing of image by OpenCV library function. In order to ensure the accuracy of image captured and processed, the camera is calibrated and corrected based on the platform. Based on MFC interface, modules such as “sub-pixel corner detection and processing,” “mouse center point extraction,” and “measurement of plane and stereoscopic distance” are developed. Combined with the OpenCV library function, a series of algorithm is developed to implement the interface function. The experimental verification and error analysis are carried out by using the captured image.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kaehler A, Bradski G (2016) Learning OpenCV 3: computer vision in C++ with the Opencv library. O’Reilly Media, Inc, America, pp 1681–1682
Albuquerque MPD, Albuquerque MPD, Chacon GT et al (2012) High-speed image processing algorithms for real-time detection of MARFEs on JET. IEEE Trans Plasma Sci 40(12):3485–3492
Wei XX, Meng L (2013) A method to implementation of lane detection under android system based on OpenCV. In: Intelligent technologies and engineering systems. Lecture notes in electrical engineering, vol 234. Springer, New York, pp 115–121
Guo ZH, Yuan JY, Wu FJ et al (2016) Research on face recognition technology based on Open CV. Electronics World, pp 105–106
Raihan F (2018) PCB defect detection USING OPENCV with image subtraction method. In: 2017 International conference on information management and technology (ICIMTech), IEEE, pp 204–209
Sasaki N, Iijima N, Uchiyama D (2015) Development of ranging method for inter-vehicle distance using visible light communication and image processing. In: 2015 15th international conference on control, automation and systems (ICCAS), IEEE, Korea, pp 666–670
Zhang H, Wang L, Jia R et al (2009) A distance measuring method using visual image processing. In: 2009 2nd international congress on image and signal processing, IEEE, China, pp 1–5
Pulli K, Baksheev A et al (2012) Real-time computer vision with OpenCV. Commun ACM 55(6):61–69
Deepthi RS, Sankaraiah S (2011) Implementation of mobile platform using Qt and OpenCV for image processing applications. In: 2011 IEEE conference on open systems, Malaysia, pp 284–289
Burden J, Cleland M et al (2010) Tracking a single cyclist during a team changeover on a velodrome track with Python and OpenCV. Procedia Eng 2(2):2931–2935
Gadhe NB, Lande BK, Meshram BB (2012) Intelligent system for detecting, modeling, classification of human behavior using image processing, machine vision and OpenCV. Int J Adv Res Comput Eng Technol 1(4):266–267
Chennamma HR, Rangarajan L (2010) Image splicing detection using inherent lens radial distortion. Int J Comput Sci Issues 7(6):149–158
Acknowledgements
This work is financially supported by the National Natural Science Foundation of China (51475282) and the Graduate Innovation Project (17KY0515).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Li, B., Xu, P. (2019). A Machine Vision-Based Multifunctional Image Processing Platform. In: Chen, S., Zhang, Y., Feng, Z. (eds) Transactions on Intelligent Welding Manufacturing. Transactions on Intelligent Welding Manufacturing. Springer, Singapore. https://doi.org/10.1007/978-981-13-3651-5_9
Download citation
DOI: https://doi.org/10.1007/978-981-13-3651-5_9
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-3650-8
Online ISBN: 978-981-13-3651-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)