Development of an inspection system for planar steel surface using multispectral photometric stereo

Kang, Dongyeop; Jang, Yu Jin; Won, Sangchul

doi:10.1117/1.oe.52.3.039701

Cited by 36 publications

(17 citation statements)

References 18 publications

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“…Kang et al [ 146 ] developed a plane steel surface detection system based on multispectral photometric stereo vision technology. The surface data were captured by a multispectral camera and an illumination system with different color channels.…”

Section: Taxonomy Of Three-dimension Defect Detection Methodsmentioning

confidence: 99%

Research Progress of Automated Visual Surface Defect Detection for Industrial Metal Planar Materials

Fang

Luo

Zhou

et al. 2020

Sensors

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The computer-vision-based surface defect detection of metal planar materials is a research hotspot in the field of metallurgical industry. The high standard of planar surface quality in the metal manufacturing industry requires that the performance of an automated visual inspection system and its algorithms are constantly improved. This paper attempts to present a comprehensive survey on both two-dimensional and three-dimensional surface defect detection technologies based on reviewing over 160 publications for some typical metal planar material products of steel, aluminum, copper plates and strips. According to the algorithm properties as well as the image features, the existing two-dimensional methodologies are categorized into four groups: statistical, spectral, model, and machine learning-based methods. On the basis of three-dimensional data acquisition, the three-dimensional technologies are divided into stereoscopic vision, photometric stereo, laser scanner, and structured light measurement methods. These classical algorithms and emerging methods are introduced, analyzed, and compared in this review. Finally, the remaining challenges and future research trends of visual defect detection are discussed and forecasted at an abstract level.

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Section: Taxonomy Of Three-dimension Defect Detection Methodsmentioning

confidence: 99%

Research Progress of Automated Visual Surface Defect Detection for Industrial Metal Planar Materials

Fang

Luo

Zhou

et al. 2020

Sensors

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“…On the other hand, iron oxide, water stains, grease and other "pseudo-defect" mostly have no deep change. There for, 3D information of surface depth is important to distinguish defects from pseudo-defects, and help to reduce the "false detection rate" [2] [3] .…”

Section: Introductionmentioning

confidence: 99%

Online Detection Technique of 3D Defects for Steel Strips Based on Photometric Stereo

Wang

Zhou

2016

2016 Eighth International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

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2D detection with gray level images is popularly employed in current surface inspection systems of steel strips, which lead to high false detection rate because of interference of pseudo-defects, such as iron oxide, water stains, and grease. Therefore, an online detection technique of 3D defects based on photometric stereo was developed in this paper. The acquired 3D information is utilized to distinguish real 3D defects from pseudo-defects, which can significant improve the performance of surface inspection system. The designed inspection system was equipped with lasers and linear CCD camera to scan the moving surface of steel strips, referred as the photometric stereo laser scanning system. Samples of hot and cold-rolled steels, with pseudo and real defects such as roll imprints, cracks and scratches on surface, were scanned and showed obvious distinguishment.

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“…This technique features two advantages: low hardware costs and low computation costs. In the field of industrial inspection, PS has improved the detection of very small surface defects [10,11]. The Lambertian model assumption is commonly used where albedo is assumed to be constant.…”

Section: Introductionmentioning

confidence: 99%

Improved Visual Inspection Through 3D Image Reconstruction of Defects Based on the Photometric Stereo Technique

Huang

et al. 2019

Sensors

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Visual inspections of nuclear power plant (NPP) reactors are important for understanding current NPP conditions. Unfortunately, the existing visual inspection methods only provide limited two-dimensional (2D) information due to a loss of depth information, which can lead to errors identifying defects. However, the high cost of developing new equipment can be avoided by using advanced data processing technology with existing equipment. In this study, a three-dimensional (3D) photometric stereo (PS) reconstruction technique is introduced to recover the lost depth information in NPP images. The system uses conventional inspection equipment, equipped with a camera and four light-emitting diodes (LEDs). The 3D data of the object surface are obtained by capturing images under multiple light sources oriented in different directions. The proposed method estimates the light directions and intensities for various image pixels in order to reduce the limitation of light calibration, which results in improved performance. This novel technique is employed to test specimens with various defects under laboratory conditions, revealing promising results. This study provides a new visual inspection method for NPP reactors.

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Development of an inspection system for planar steel surface using multispectral photometric stereo

Cited by 36 publications

References 18 publications

Research Progress of Automated Visual Surface Defect Detection for Industrial Metal Planar Materials

Research Progress of Automated Visual Surface Defect Detection for Industrial Metal Planar Materials

Online Detection Technique of 3D Defects for Steel Strips Based on Photometric Stereo

Improved Visual Inspection Through 3D Image Reconstruction of Defects Based on the Photometric Stereo Technique

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