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All Journal International Journal of Electrical and Computer Engineering
Young Woon Woo
Dong-Eui University
Computer Science & IT Electrical & Electronics Engineering

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Defect Detection in Ceramic Images Using Sigma Edge Information and Contour Tracking Method Kwang-Baek Kim; Young Woon Woo
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 1: February 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1366.601 KB) | DOI: 10.11591/ijece.v6i1.pp160-166

Abstract

In this paper, we suggest a method of detecting defects by applying Hough transform and least squares on ceramic images obtained from non-destructive testing. In the ceramic images obtained from non-destructive testing, the background area, where the defect does not exist, commonly shows gradual change of luminosity in vertical direction. In order to extract the background area which is going to be used in the detection of defects, Hough transform is performed to rotate the ceramic image in a way that the direction of overall luminosity change lies in the vertical direction as much as possible. Least squares is then applied on the rotated image to approximate the contrast value of the background area. The extracted background area is used for extracting defects from the ceramic images. In this paper we applied this method on ceramic images acquired from non-destructive testing. It was confirmed that extracted background area could be effectively applied for searching the section where the defect exists and detecting the defect.
Automatic segmentation of large bowl obstruction area with hough transform from erect abdominal radiograph images Kwang Baek Kim; Doo Heon Song; Young Woon Woo
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2674-2679

Abstract

Large bowel obstruction is less frewuent but often appears acute and needs emergent treatment. Erect abdominal radiograph is usually the first imaging study performed in patients suspected of having large bowel obstruction. However, that mordality suffers from operator subjectivity thus a fully automatic computer aied tool is necessary. In this paper, we peopose an automatic large bowel feature (air-fluid region) segmentation method based on Canny edge detection and Hough transform. In experiment, the proposed method was successful in finding target region from large bowel obstruction patients’ radiographic images in all 30 cases provided. Whilie limited only applicable to the large bowel obstruction cases, the proposed method is practically feasible in application.
Co-Authors Doo Heon Song Kwang Baek Kim Kwang-Baek Kim