• Journal of the Korean Society for Precision Engineering
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• v.16 no.8
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• pp.16-22
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• 1999

In this paper, an efficient algorithm for estimating real edge locations to subpixel values is described. Digital images are acquired by projection into image plane and sampling process. However, most of real edge locations are lost in this process, which causes low measurement accuracy. For accurate measurement, we propose an algorithm which estimates the real boundary between two adjacent pixels in digital imagery, with subpixel accuracy. We first define 1D edge operator based on the moment invariant. To extend it to 2D data, the edge orientation of each pixel is estimated by the LSE(Least Squares Error)line/circle fitting of a set of pixels around edge boundary. Then, using the pixels along the line perpendicular to the estimated edge orientation the real boundary is calculated with subpixel accuracy. Experimental results using real images show that the proposed method is robust in local noise, while maintaining low measurement error.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.493-498
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• 2007

In this paper, a 2-dimensional accurate edge-based matching algorithm using subpixel edges is proposed that combines the Generalized Hough Transform(GHT) and the Chamfer matching to complement the weakness of either method. First, the GHT is used to find the approximate object positions and orientations, and then these positions and orientations are used as starting parameter values to find more accurate position and orientation using the Chamfer matching with distance interpolation. Finally, matching accuracy is further refined by using a subpixel algorithm. Testing results demonstrate that greater matching accuracy is achieved using subpixel edges rather than edge pixels.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.105-108
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• 1996

In this paper, we present an interpolation schema for image resolution enhancement using fuzzy logic. Proposed algorithm can recover both low and high frequency information in image data. In general, interpolation techniques are based on linear operators which are essentially details in the original image. In our fuzzy approach, the operator itself balances the strength of its sharpening and noise suppressing components according to the properties of the input image data. The proposed interpolation algorithm is performed in three step. First logic reasoning is applied to coarsely interpret the high frequency information. These results are combined to obtain the optical output. Using our approach, resolution of the original image can be applied to various kind of image processing topics such as image enhancement, subpixel edge detection, and filtering.

• IE interfaces
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• v.11 no.3
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• pp.15-22
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• 1998

A new improved algorithm in edge location to subpixel accuracy using decent-based weight to spatial information is proposed in this paper and applied to automated visual inspection(AVI) system. An application of the new edge operator as an edge detector is also provided and compared with Tabatabai and Lyvers edge detectors. The existing algorithms located edger to subpixel accuracy using least-square or moment-based methods. The algorithms also use only spatial information or grey-level values to locate edges. However, the proposed algorithm consider the weighted sum of grey-levels values of each edge pattern. The results show that the proposed algorithm is relatively less biased and has smaller standard deviation than the edge operations developed by Tabatabai and Lyvers in the presence of noise.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.503-513
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• 2020

This paper presents a method to evaluate denoising filters based on edge locations in their denoised images. Image quality assessment has often been performed by using structural similarity (SSIM). However, SSIM does not provide clearly the geometric accuracy of features in denoised images. Thus, in this paper, a method to localize edge locations with subpixel accuracy based on adaptive weighting of gradients is used for obtaining the subpixel locations of edges in ground truth image, noisy images, and denoised images. Then, this paper proposes a method to evaluate the geometric accuracy of edge locations based on root mean squares error (RMSE) and jaggedness with reference to ground truth locations. Jaggedness is a measure proposed in this study to measure the stability of the distribution of edge locations. Tested denoising filters are anisotropic diffusion (AF), bilateral filter, guided filter, weighted guided filter, weighted mean of patches filter, and smoothing filter (SF). SF is a simple filter that smooths images by applying a Gaussian blurring to a noisy image. Experiments were performed with a set of simulated images and natural images. The experimental results show that AF and SF recovered edge locations more accurately than the other tested filters in terms of SSIM, RMSE, and jaggedness and that SF produced better results than AF in terms of jaggedness.

• Korean Journal of Remote Sensing
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• v.32 no.1
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• pp.13-24
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• 2016

This paper presents a method to evaluate the performance of subpixel localization operators using target image data. Subpixel localization of edges is important to extract the precise shape of objects from images. In this study, each target image was designed to provide reference lines and edges to which the localization operators can be applied. We selected two types of moment-based operators: Gray-level Moment (GM) operator and Spatial Moment (SM) operator for comparison. The original edge localization operators with kernel size 5 are tested and their extended versions with kernel size 7 are also tested. Target images were collected with varying Camera-to-Object Distance (COD). From the target images, reference lines are estimated and edge profiles along the estimated reference lines are accumulated. Then, evaluation of the performance of edge localization operators was performed by comparing the locations calculated by each operator and by superimposing them on edge profiles. Also, enhancement of edge localization by increasing the kernel size was also quantified. The experimental result shows that the SM operator whose kernel size is 7 provides higher accuracy than other operators implemented in this study.

• Journal of the Optical Society of Korea
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• v.17 no.5
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• pp.392-398
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• 2013

As the essential techniques for the CD (Critical Dimension) measurement of the LCD pattern, there are various modules such as an optics design, auto-focus [1-4], and precise edge detection. Since the operation of image enhancement to improve the CD measurement repeatability, a ring type of the reflected lighting optics is devised. It has a simpler structure than the transmission light optics, but it delivers the same output. The edge detection is the most essential function of the CD measurements. The CD measurement is a vital inspection for LCDs [5-6] and semiconductors [7-8] to improve the production yield rate, there are numbers of techniques to measure the CD. So in this study, a new subpixel algorithm is developed through facet modeling, which complements the previous sub-pixel edge detection algorithm. Currently this CD measurement system is being used in LCD manufacturing systems for repeatability of less than 30 nm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.379-383
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• 1995

In this paper, vision inspection module for dimensional measurement has been developed. For high accuracy of CMM, camera calibration and edge detection with subpixel accuracy have been implemented. In measurement process, the position of vision probe can be recognized in PC by serial communication with CMM controller. The developed vision inspection module can be widely applied to the practical measurement process.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.94-99
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• 2007

In this paper, a 2-dimensional edge-based matching algorithm is proposed that combines the generalized Hough transform (GHT) and the Chamfer matching to complement weakness of either method. First, the GHT is used to find approximate object positions and orientations, and then these positions and orientations are used as starling parameter values to find more accurate position and orientation using the Chamfer matching. Finally, matching accuracy is further refined by using a subpixel algorithm. The algorithm was implemented and successfully tested on a number of images containing various electronic components.

• Proceedings of KOSOMES biannual meeting
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• 2005.11a
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• pp.197-202
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• 2005

Generally, a semiconductor chip measured with a few micro units is captured by line scan camera for higher inspection accuracy. However, the faulty inspection requires an exact boundary detection algorithm because it is very sensitive to scan speed and lighting conditions. In this paper we propose boundary detection using subpixel edge detection method in order to increase the accuracy of bump faulty detection on chips. The bump edge is detected by first derivative to four directions from bump center point and the exact edge positions are searched by the subpixel method. Also, the exact bump boundary to calculate the actual bump size is computed by LSM(Least Squares Method) to minimize errors since the bump size is varied such as bump protrusion, bump bridge, and bump discoloration. Experimental results exhibit that the proposed algorithm shows large improvement comparable to the other conventional boundary detection algorithms.