• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.1
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• pp.139-148
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• 2015

In this paper, a new algorithm is proposed for detecting the product number of each thick plate and extracting each character of the product number from a image which contains several thick plates. In general, a image of thick plates contains several steal plates. To obtain the product number from the image, we first need to separate each plate. To do so, we use the line edges of thick plates and a clustering algorithm. After separating each plate, background parts are eliminated from the image of each plate. Background parts of an individual thick plate image consist of the dark part of steel and the white part of paint which is used for printing the product number. We propose a two-tiered method where dark background parts are first eliminated and then white parts are eliminated. Finally, each character is extracted from the product number image using the characteristics of product number. The results of the experiments on the various steal plates images emphasize that the proposed algorithm detects each thick plate and extracts the product number from a image effectively.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1033-1039
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• 2012

In this paper, a simple and robust algorithm is proposed for detecting each steel plate from a image which contains several steel plates. Steel plate is characterized by line edge, so line detection is a fundamental task for analyzing and understanding of steel plate images. To detect the line edge, the proposed algorithm uses the small eigenvalue analysis. The proposed approach scans an input edge image from the top left corner to the bottom right corner with a moving mask. A covariance matrix of a set of edge pixels over a connected region within the mask is determined and then the statistical and geometrical properties of the small eigenvalue of the matrix are explored for the purpose of straight line detection. Using the detected line edges, each plate is determined based on the directional information and the distance information of the line edges. The results of the experiments emphasize that the proposed algorithm detects each steel plate from a image effectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1479-1486
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• 2011

In this paper, a simple and robust algorithm is proposed for detecting straight line segments in a steel plate image. Line detection from a steel plate image is a fundamental task for analyzing and understanding of the image. The proposed algorithm is based on small eigenvalue analysis. The proposed approach scans an input edge image from the top left comer to the bottom right comer with a moving mask. A covariance matrix of a set of edge pixels over a connected region within the mask is determined and then the statistical and geometrical properties of the small eigenvalue of the matrix are explored for the purpose of straight line detection. Before calculating the eigenvalue, each line segment is separated from the edge image where several line segments are overlapped to increase the accuracy of the line detection. Additionally, unnecessary line segments are eliminated by the number of pixels and the directional information of the detected line edges. The respects of the experiments emphasize that the proposed algorithm outperforms the existing algorithm which uses small eigenvalue analysis.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.115-115
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• 2009

아연코팅강판의 레이저 용접시 발생하는 용접결함은 이미 널리 알려진 이슈이다. 그러나 대부분의 연구가 박판을 중심으로 이루어지고 있어서, 후판을 중심으로 한 조선산업에서의 아연코팅 강판의 연구는 매우 미진한 실정이다. 이중 후판 아연코팅강판의 결함검출연구는 그 연구가 거의 전무한 실정으로, 본 연구에서는 후판 아연코팅강판의 레이저 겹치기용접시의 결함검출을 중심으로 실험을 실시하였다. 실험은 Fig. 1에서와 같이 광신호와 음향신호의 RMS를 통하여 raw signal에서 잘 나타나지 않았던 신호의 패턴을 확인함으로써 실제 신호와 비드와를 대응을 가능하게 하였다. 또한 결함 발생시의 RMS값을 건전한 상태와 비교분석하여 실제 결함검출의 가능성도 확인할 수 있었다.

• Proceedings of the KWS Conference
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• 2006.10a
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• pp.286-288
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• 2006

• Korean Journal of Metals and Materials
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• v.47 no.1
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• pp.7-12
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• 2009

The detailed quantitative microstructural data on the cracking of coarse constituent particles in 7075 (T651) series wrought Al-alloys have been studied using the utility of a novel digital image processing technique, where the particle cracks are generated due to monotonic loading. The microstructural parameters such as number density, volume fraction, size distribution, first nearest neighbor distribution, and two-point correlation function have been quantitatively characterized using the developed technique and such data are very useful to verify and study the theoretical models for the damage evolution and fracture of Al-alloys. The data suggests useful relationships for damage modeling such as a linear relationship between particle cracking and strain exists for the uniaxial tensile loading condition, where the larger particles crack preferentially.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.05a
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• pp.264-267
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• 2006

One of the serious problems that make the flaw identification in a multi-layered thick composite panel more difficult is the interferenceeffect of the upper layer. To take care of such a problem, here we propose an image enhancement approach that can get rid of such an interference effect to ultrasonic C-scan images by a normalization of the acquired signals by a reference signals, and demonstrate its performance in the experiments. Specifically, three specimens with artificial flaws are prepared and ultrasonic C-scan images are acquired experimentally to eliminate the undesired interference effect. Cleat successes are observed in the present study demonstrating the high potential of the proposed algorithm as a practical image enhancement tool in many practical situations.