Sub-pixel accuracy by optical measurement of large automobile components

Stanke, Gerd; Zedler, L.; Zorn, A.; Weckend, F.; Weide, H.-G.

doi:10.1109/iecon.1998.724107

Cited by 4 publications

(5 citation statements)

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“…One of them is approach used by Stanke [23] or Ji [24] where subpixel edge position is indicated by center of gravity of a gradient peak. Bie and Liu [25] applied quad-tree decomposition to divide pixels into subpixels while Kisworo [6] determined subpixel edge using image energy computed based on image intensities and their Hilbert transform.…”

Section: Other Methodsmentioning

confidence: 99%

Gaussian-Based Approach to Subpixel Detection of Blurred and Unsharp Edges

Fabijańska

2014

Annals of Computer Science and Information Systems

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Abstract-In this paper the problem of edge detection with subpixel accuracy is considered. In particular, the precise detection of significantly blurred edges is regarded. A new method for subpixel edge detection is introduced. The method attempts to reconstruct image gradient function at the edge using the Gaussian function. The results of subpixel edge detection in the artificially created and the real images obtained by the introduced approach are presented and compared with the results of previously proposed methods. In particular, the moment based methods, the gravity center method and the parabola fitting method are considered in the comparison. The presented results prove the robustness of the introduced approach against the averaging and the Gaussian blur. Additionally, the comparison shows, that the introduced approach outperforms the existing state-of-art methods for subpixel edge detection. I. INTRODUCTIONDGE detection is the problem of crucial importance in image processing. Edges define location and geometric features of objects present in the scene. Therefore, in a typical vision system, edge detection is performed during low level processing and provides information for operations performed in the following stages, such as quantitative analysis, target recognition or image coding etc.Recently, the requirements for edge detection accuracy rapidly increase. Satellite remote sensing, telemetry, photogrammetry, medical image analysis, industrial inspection, geometrical measurement and other applications where accuracy is at premium require precision of tenths or even hundredths of pixel.The traditional, well-established methods for edge detection such as gradient operators (Sobel, Prewitt, Roberts), Canny edge detector, operator LoG etc. all belong to pixel level. Therefore, they are mostly insufficient for practical applications of modern machine vision. Due to their low precision of edge location and extracted wider edges, these approaches more and more often have difficulties in meeting the actual accuracy requirements of vision systems. Therefore, the development of subpixel techniques for edge detection has become one of the hotspots of the current This work was not supported by any organization research in image processing. Some work has already been done on this problem. However, the major methods for subpixel edge detection are still to be developed. It should be also underlined that while there has been substantial work performed on the detection of clear and well defined edges at subpixel accuracy, a little has been done on the subpixel edge detection in low contrast images containing blurred, noisy and unsharp edges [1] [2]. This paper presents a new method which is a step forward through introducing subpixel analysis into edge detection. In particular, it considers precise edge detection of significantly blurred edges. As the already proposed methods deal mostly with sharp, regular and well defined edges the introduced approach can be considered like a novelty. This paper is organized as f...

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Section: Other Methodsmentioning

confidence: 99%

Gaussian-Based Approach to Subpixel Detection of Blurred and Unsharp Edges

Fabijańska

2014

Annals of Computer Science and Information Systems

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“…Stanke et al (1998) proposed a method which determines the edge location at the subpixel level using the center of gravity of the gradient peak. A similar approach was also used by Ji et al (2009).…”

Section: Other Methodsmentioning

confidence: 99%

A survey of subpixel edge detection methods for images of heat-emitting metal specimens

Fabijańska

2012

International Journal of Applied Mathematics and Computer Science

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In this paper the problem of accurate edge detection in images of heat-emitting specimens of metals is discussed. The images are provided by the computerized system for high temperature measurements of surface properties of metals and alloys. Subpixel edge detection is applied in the system considered in order to improve the accuracy of surface tension determination. A reconstructive method for subpixel edge detection is introduced. The method uses a Gaussian function in order to reconstruct the gradient function in the neighborhood of a coarse edge and to determine its subpixel position. Results of applying the proposed method in the measurement system considered are presented and compared with those obtained using different methods for subpixel edge detection.

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“…When the ratio between the object size and camera distance increases, some kind of a thickness correction mechanism must be used. However, Stanke et al present a simple algorithmic correction mechanism that could be used [9].…”

Section: Discussion Referencesmentioning

confidence: 99%

“…Optical measurement of such large two-dimensional parts has been studied by Stanke et al [9]. They state the following requirements: handling of large parts, complete contour measurement, fast image acquisition, precision ranging to 0.2 mm, conversion of the result in a CAD-like format, and low cost implementation.…”

Section: Introductionmentioning

confidence: 99%

High precision 2-D geometrical inspection

Kyrki

Kalvianen

Proceedings 15th International Conference on Pattern Recognition. ICPR-2000

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Automated visual inspection has become important ,for modern industry mainly because production rates and the level of automation have continually increased. This paper presents a system for automated visual inspection of large two-dimensional parts. The system is capable of inspecting sheet metal parts using CAD data. The inspection is performed based on a CAD model. There are existing systems that perform this function but they are not particularly well suitable for in-place inspection. In the proposed system, the high precision inspection of individual features is performed by firstly estimating the global position of a part. Next, each local feature is measured using subpixel techniques. Finally, the measurements are compared with a CAD model. Experiments are presented to evaluate the precision of system components. According to the results, the calibration procedure seems to be the factor that has the greatest effect on the final precision. Last, a comparison to similar systems is made and some suggestions are given how the precision could be further improved.

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Sub-pixel accuracy by optical measurement of large automobile components

Cited by 4 publications

References 1 publication

Gaussian-Based Approach to Subpixel Detection of Blurred and Unsharp Edges

Gaussian-Based Approach to Subpixel Detection of Blurred and Unsharp Edges

A survey of subpixel edge detection methods for images of heat-emitting metal specimens

High precision 2-D geometrical inspection

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