Improved illumination for vision-based defect inspection of highly reflective metal surface

Li, Lin; Wang, Zhong; Pei, Fangying; Wang, Xiangjun

doi:10.3788/col201311.021102

Cited by 29 publications

(6 citation statements)

References 6 publications

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“…The basic concept of INMI-based methods [21][22][23][24][25][26][27][28][29][66][67][68] is to obtain images of the real measured workpieces, which can be represented in the form of grayscale images through visual detection under the SL system to complete the image acquisition of the measured workpieces.…”

Section: Inmi Methodsmentioning

confidence: 99%

“…Quan et al designed an array pattern hole template, which can realize the batch feeding, rolling and detection of steel balls, and cooperates with SL equipment to solve the problems of the reflection of the polished surface of steel balls and the mutual projection between them [25]. Li et al designed a circular diffuse dome light source based on LEDs [26]. To eliminate the shadows formed by surrounding objects and reflect bright spots, a circular LED array was designed that had a dome-shaped diffuse reflection wall above the circular LED array.…”

Section: Inmi Methodsmentioning

confidence: 99%

“…(a) Single sensors: This kind of sensor is used to sense real information about HRRS defects. In HRRS DDSs, various single sensors have been used such as fiber optic sensors [11][12][13], an ultrasonic probe [14], capacitance sensors [ 15,16], vision sensors [3,4,[17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32], etc. It is difficult to achieve rapid, accurate and comprehensive detection of HRRS defects using single sensor-based detection methods.…”

Section: Types Of Sensorsmentioning

confidence: 99%

See 2 more Smart Citations

Defect detection for highly reflective rotary surfaces: an overview

Zhou

Pingge

et al. 2021

Meas. Sci. Technol.

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Defects over a highly reflective rotary surface (HRRS) may change the service performance, lifespan and safety properties of products. Therefore, defect detection is very important for surface quality assurance. In this paper, the attributes of HRRS defect detection are described. Then, a comparative overview in terms of key parameters in the HRRS defect detection systems is elaborated. Finally, this paper reviews various detection technologies for HRRS defect detection and categorizes the previous literature by their detection technologies, which can provide a reference for further implementation and improvements in this field. This study provides guidelines for selecting which scheme is the most suitable when designing new HRRS defect detection systems.

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Section: Inmi Methodsmentioning

confidence: 99%

Section: Inmi Methodsmentioning

confidence: 99%

Section: Types Of Sensorsmentioning

confidence: 99%

See 1 more Smart Citation

Defect detection for highly reflective rotary surfaces: an overview

Zhou

Pingge

et al. 2021

Meas. Sci. Technol.

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“…The segmentation object in this paper is a magnesium ingot with a trapezoidal cross-section, and the specific dimensions are shown in Figure 1 a. The surface of the target magnesium ingot is smooth and local overexposure will occur in the acquired image under a complex external light environment [ 8 ]. When the image is segmented, the gradient of partial gray value information of the magnesium ingot changes dramatically, and the segmentation result of the magnesium ingot obtained by traditional methods is incomplete.…”

Section: Introductionmentioning

confidence: 99%

Magnesium Ingot Stacking Segmentation Algorithm for Industrial Robot Based on the Correction of Image Overexposure Area

Li,

Zheng,

Wang

et al. 2023

Sensors

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This paper proposes an adaptive threshold segmentation algorithm for the magnesium ingot stack based on image overexposure area correction (ATSIOAC), which solves the problem of mirror reflection on the surface of magnesium alloy ingots caused by external ambient light and auxiliary light sources. Firstly, considering the brightness and chromaticity information of the mapped image, we divide the exposure probability threshold into weak exposure and strong exposure regions. Secondly, the saturation difference between the magnesium ingot region and the background region is used to obtain a mask for the magnesium ingot region to eliminate interference from the image background. Then, the RGB average of adjacent pixels in the overexposed area is used as a reference to correct the colors of the strongly exposed and weakly exposed areas, respectively. Furthermore, in order to smoothly fuse the two corrected images, pixel weighted average (WA) is applied. Finally, the magnesium ingot sorting experimental device was constructed and the corrected top surface image of the ingot pile was segmented through ATSIOAC. The experimental results show that the overexposed area detection and correction algorithm proposed in this paper can effectively correct the color information in the overexposed area, and when segmenting ingot images, complete segmentation results of the top surface of the ingot pile can be obtained, effectively improving the accuracy of magnesium alloy ingot segmentation. The segmentation algorithm achieves a segmentation accuracy of 94.38%.

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“…However, it can only be applied for sampling checks, but not for 100% checks. Li et al [8] presented an improved optical illumination model. Experiment results showed that the designed illumination system has higher defect expressivity.…”

Section: Introductionmentioning

confidence: 99%

A real-time surface inspection system for precision steel balls based on machine vision

Yi-ji

Tsai

Hsu³

2016

Meas. Sci. Technol.

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Precision steel balls are one of the most fundament components for motion and power transmission parts and they are widely used in industrial machinery and the automotive industry. As precision balls are crucial for the quality of these products, there is an urgent need to develop a fast and robust system for inspecting defects of precision steel balls. In this paper, a real-time system for inspecting surface defects of precision steel balls is developed based on machine vision. The developed system integrates a dual-lighting system, an unfolding mechanism and inspection algorithms for real-time signal processing and defect detection. The developed system is tested under feeding speeds of 4 pcs s−1 with a detection rate of 99.94% and an error rate of 0.10%. The minimum detectable surface flaw area is 0.01 mm2, which meets the requirement for inspecting ISO grade 100 precision steel balls.

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Improved illumination for vision-based defect inspection of highly reflective metal surface

Cited by 29 publications

References 6 publications

Defect detection for highly reflective rotary surfaces: an overview

Defect detection for highly reflective rotary surfaces: an overview

Magnesium Ingot Stacking Segmentation Algorithm for Industrial Robot Based on the Correction of Image Overexposure Area

A real-time surface inspection system for precision steel balls based on machine vision

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