A simple method for dimensional measurement of ring-shaped objects using image processing technique

Dang, Anh-Tuan; Hsu, Quang‐Cherng; Truong, Tat-Tai

doi:10.1007/s00170-021-07416-5

Cited by 7 publications

(5 citation statements)

References 23 publications

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“…The application of image processing for automatically making measurements can enhance the efficiency of this process by allowing more parts to be measured within the same time frame, while also mitigating measurement discrepancies that can result from human error [3]. One approach for automating measurement processes involves integrating computer vision and photogrammetry techniques.…”

Section: Introductionmentioning

confidence: 99%

“…Photogrammetry involves deriving three-dimensional geometry from photographic images [7,8]. Photogrammetry has found successful applications in various domains, e.g., for unmanned aerial vehicles and satellite mapping [9], bridge monitoring [7], threedimensional object reconstruction [10], 3D scene mapping [11], and precise object measurements [3,[12][13][14][15][16][17]. This field of study has versatile applications in many industries including geology, architecture, topography, automotive engineering, and aerospace [8].…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies have addressed object dimension measurement using Monocular Machine Vision, with various applications such as measuring critical dimensions in LCDs [14], evaluating the edges of heat-emitting metals [15], measuring gears [13], measuring elements on the contours of ring-shaped objects [3], and measuring shafts [12,16,17].…”

Section: Introductionmentioning

confidence: 99%

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A Cost-Effective Method for Automatically Measuring Mechanical Parts Using Monocular Machine Vision

Barca

Pimenta

2023

Sensors

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Automatic measurements via image processing can accelerate measurements and provide comprehensive evaluations of mechanical parts. This paper presents a comprehensive approach to automating evaluations of planar dimensions in mechanical parts, providing significant advancements in terms of cost-effectiveness, accuracy, and repeatability. The methodology employed in this study utilizes a configuration comprising commonly available products in the industrial computer vision market, therefore enabling precise determinations of external contour specifications for mechanical components. Furthermore, it presents a functional prototype for making planar measurements by incorporating an improved subpixel edge-detection method, thus ensuring precise image-based measurements. The article highlights key concepts, describes the measurement procedures, and provides comparisons and traceability tests as a proof of concept for the system. The results show that this vision system did achieve suitable precision, with a mean error of 0.008 mm and a standard deviation of 0.0063 mm, when measuring gauge blocks of varying lengths at different heights. Moreover, when evaluating a circular sample, the system resulted in a maximum deviation of 0.013 mm, compared to an alternative calibrated measurement machine. In conclusion, the prototype validates the methods for planar dimension evaluations, highlighting the potential for enhancing manual measurements, while also maintaining accessibility. The presented system expands the possibilities of machine vision in manufacturing, especially in cases where the cost or agility of current systems is limited.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Cost-Effective Method for Automatically Measuring Mechanical Parts Using Monocular Machine Vision

Barca

Pimenta

2023

Sensors

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“…Shape reconstruction is based on planar rectification and collation of laser profiles, and not on triangulation. The final paper [18] included in the second part of the scientific literature review proposes a method for reconstructing the two-dimensional profiles of ring-shaped objects using image processing, resulting in a point cloud consisting of outer and inner contours that can be directly used for automated measurement.…”

Section: Introductionmentioning

confidence: 99%

Possibilities of Evaluating the Dimensional Acceptability of Workpieces Using Computer Vision

Svalina

Turinski

Grgić

et al. 2023

Teh. glas. (Online)

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This paper discusses the possibilities of an automated solution for determining dimensionally accurate and defective products using a computer vision system. In a real industrial environment, research was conducted on a prototype of a quality control machine, i.e. a machine that, based on product images, evaluates whether the product is accurate or defective using computer vision. Various geometric features are extracted from the obtained images of products, on the basis of which a fuzzy inference system based on Fuzzy C-means clustering features is created. The extracted geometric features represent the input variables, and the output variable has two values - true and false. The root mean square error in the evaluation of the accuracy and defectiveness of products ranges between 0.07 and 0.16. Through this research, valuable findings and conclusions were reached for the future research, since this topic is poorly examined in the most renowned databases.

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“…They matched the feature points through FAST and BRIEF, mapped the feature points to the world coordinate system based on binocular vision, and calculated the size according to the feature points in the world coordinate system. Dang et al 8 proposed a method to measure the size of large circular objects by using an image processing technology. The size of the parts is determined through the position relationship between the known landmarks and the parts in the background by using the contrast method.…”

Section: Introductionmentioning

confidence: 99%

Visual measurement of the bearing diameter based on the homography matrix and partial area effect

Jiang

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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A measurement method based on the homography matrix and partial area effect is studied to improve the precision of the visual measurement of the bearing size. Firstly, the camera is calibrated to obtain its distortion coefficient, and the image is corrected for distortion. Secondly, the relationship between the pixel plane and the bearing imaging plane is determined by solving the homography matrix with a chessboard. Finally, the sub-pixel edge contour of the bearing is obtained through the improved partial area effect, and the pixel coordinates are mapped to the world coordinates according to the homography matrix. The feature size is obtained by fitting the mapping points. Experimental results showed that the transformation of the homography matrix is more accurate than the pixel equivalent in the process of converting the pixel size to the actual size. The improved partial area effect sub-pixel edge detection results are better than the partial area effect and Zernike moment. The measurement error for the bearing outer diameter is less than 0.05 mm and is within 0.5 pixel.

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A simple method for dimensional measurement of ring-shaped objects using image processing technique

Cited by 7 publications

References 23 publications

A Cost-Effective Method for Automatically Measuring Mechanical Parts Using Monocular Machine Vision

A Cost-Effective Method for Automatically Measuring Mechanical Parts Using Monocular Machine Vision

Possibilities of Evaluating the Dimensional Acceptability of Workpieces Using Computer Vision

Visual measurement of the bearing diameter based on the homography matrix and partial area effect

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