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http://dx.doi.org/10.33851/JMIS.2021.8.2.93

An Image Quality Evaluation Model for Optical Strip Signal-to-Noise Ratio in the Target Area of High Temperature Forgings

Ma, Hongtao (School of Mechanical Engineering and Automation, Dalian Polytechnic University)
Zhao, Yuyang (School of Mechanical Engineering and Automation, Dalian Polytechnic University)
Feng, Yiran (School of Mechanical Engineering and Automation, Dalian Polytechnic University)
Lee, Eung-Joo (Dept. of Information and Communication Engineering, Tongmyong University)
Tao, Xueheng (School of Mechanical Engineering and Automation, Dalian Polytechnic University)

Publication Information

Journal of Multimedia Information System / v.8, no.2, 2021 , pp. 93-100 More about this Journal

Abstract

Under the time-varying temperature, the high-temperature radiation of forgings and the change of reflection characteristics of oxide skin on the surface of forgings lead to the difficulty of obtaining images to truly reflect the geometric characteristics of forgings. It is urgent to study the clear and reliable acquisition method of hot forging feature image under time-varying temperature to meet the requirements of visual measurement of hot geometric parameters of forgings. Based on this, this chapter first puts forward the quality evaluation method of forging feature image, which provides guarantee for the accurate evaluation of feature image quality. Furthermore, the factors that affect the image quality, such as the radiation characteristics of forgings and the photographic characteristics of cameras, are analyzed, and the imaging spectrum which can effectively suppress the radiation intensity of forgings is determined. Finally, aiming at the problem that the quality of image acquisition is difficult to guarantee due to the drastic change of radiation intensity of forgings under time-varying temperature, an image acquisition method based on minimum signal-to-noise ratio (SNR) based laser light intensity adaptation is proposed, which significantly improves the definition of feature light strips in forging images at high temperature, and finally realizes the clear acquisition of feature images of large-scale hot forging under time-varying temperature.

Keywords

Volume rendering high; Temperature forging images; Quality evaluation; Signal to noise ratio;

Citations & Related Records

Reference

1	V. H. Gaidhane, Y. V. hote, and V. Singh, "An efficient similarity measure approach for PCB surface defect detection," Pattern Analysis and Applications, vol. 17, no. 21, pp. 277-289, 2018.
2	Z. Chi, "Light strip extraction method in laser assisted visual measurement of hot forging," M.S. thesis. Dalian University of technology, 2015.
3	K. Tuongmtn, "Automatic image thresholding using Otsu's method and entropy weighting scheme for surface defect detection," Soft Computing, vol. 17, no. 22, pp. 4197-4203, 2018.
4	Z. Peng, "Research and development of machine vision," Science Press, 2012.
5	Gonzalez, "Digital image processing," Electronic Industry Press, 2003.
6	A. Serir, A. Beghdadi, and F. Kerouh, "No-reference blurimage quality measure based on multiplicative multiresolution decomposition," Journal of Visual Image Representation, vol. 24, no. 7, pp. 911-925, 2013. DOI
7	G. Jinhui, "Development status of surface reconstruction algorithm," Journal of Tonghua Normal University, vol. 13, no. 24, pp. 2-13, 2003.
8	Byung-Gyu Kim, Jae-Ick Shim, and Dong-Jo Park, "Fast image segmentation based on multi-resolution analysis and wavelets," Pattern Recognition Letters, vol. 24, no. 15, pp. 2995-3006, Nov. 2003. DOI
9	W. Withayachumnankul, R. Kunako, P. Nvong, C. Asavathongkul, and P. Sooraksa, "Rapid detection of hairline cracks on the surface of piezoelectric ceramics," International Journal of Advanced Manufacturing Technology, vol. 12, no. 64, pp. 1275-1283, 2013.