• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.6
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• pp.451-459
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• 2016

Crack detection on panels during manufacturing process is an important step for ensuring the product quality. The accuracy and efficiency of traditional crack detection methods, which are performed by eye inspection, are dependent on human inspectors. Therefore, implementation of an on-line and precise crack detection is required during the panel pressing process. In this paper, a regular CCTV camera system is utilized to obtain images of panel products and an image process based crack detection technique is developed. This technique uses a comparison between the base image and a test image using an amplitude mapping of the local image. Experiments are performed in the laboratory and in the actual manufacturing lines to evaluate the performance of the developed technique. Experimental results indicate that the proposed technique could be used to effectively detect a crack on panels with high speed.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.321-323
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• 2006

The light gets darker from center to edge of the light source. Therefore, we can find the center of the sun using shading histogram. Moreover, we can track the exact position of the sun with the shading histogram. In this paper, we propose a new technique using image-processing of digital camera, in order to locate the position of the sun.

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.3
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• pp.34-42
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• 1994

The present study is aimed to improve the PIV performance by suggesting a two-frame particle identification technique and by introducing estimation method of wall pressure distribution from the velocity data. Adopted image processing system consists of one commercial image board slit into a personal computer, 2-D sheet light generator, flow picture recording apparatus and related particle identification software. A revised particle tracking method essential to PIV performance is obtained by particle centroid correlation pairing (CCP) and its effectiveness is ascertained by comparison with multi-frame identification.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.8
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• pp.108-114
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• 2003

This research describes a image-processing technique for the scratch detecting algorithm for ITO coated glass. We use the modified logical thresholding method (called adaptive logical thresholding method) for binarization of gray-scale glass image. This method is useful to the algorithm for detecting the scratch of ITO coated glass automatically without need of any prior information of manual fine-tuning of parameters.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.03a
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• pp.213-216
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• 1997

The measurement of 3D surface strain using the image processing method is another approach for strain measurement. The advantage of this method is that strains at several points included in a captured image can be obtained automatically from only one process. In this study, the whole process of automated surface strain measurement is presented. The strain distribution on a LDH specimen is illustrated as a result of the trial to develope an automated strain measurement system.

• Journal of Biosystems Engineering
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• v.24 no.1
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• pp.51-58
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• 1999

A color image processing algorithm was developed to assist the robotic plug-seedling transplanter. The algorithm was designed to identify and locate empty cells in the seedling tray. The image of pepper seedling tray was segmented into regions of plant, frame and soil using thresholding technique which utilized HSI or RGB color characteristics of each region. The detection algorithm was able to successfully identify empty cells and locate their two-dimensional location. The overall success rate of the algorithm was about 88%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.99-110
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• 2005

These days, many image processing techniques have been studied for effective image compression. Among those, The 2D image filtering is widely used for 2D image processing. The 2D image filtering can be implemented by performing the 1D linear filter separately in the horizontal and vertical direction. Efficiency of image compression depends on what filtering method is used. Generally, circular convolution is widely used in 2D image filtering for image processing. However it doesn't consider correlations at the boundary region of image, therefore effective filtering can not be performed. To solve this problem. I proposed new convolution technique using loop convolution which satisfies the 'alias-free' and 'error-free' requirement in the reconstructed image. This method could provide more effective compression performance than former methods because it used highly-correlated data when performed at the boundary region. In this paper, Sub-band Coding(SBC) was adopted to analyze efficiency of proposed filtering technique, and the simulator developed by Java-based language was used to examine the performance of proposed method.

• Ocean and Polar Research
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• v.35 no.3
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• pp.239-247
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• 2013

Digital image processing is a process to analyze a large volume of information on digital images. In this study, Artemia hatching rate was measured by automatically classifying and counting cysts and larvae based on color imaging data from cyst hatching experiments using an image processing technique. The Artemia hatching rate estimation consists of a series of processes; a step to convert the scanned image data to a binary image data, a process to detect objects and to extract their shape information in the converted image data, an analysis step to choose an optimal discriminant function, and a step to recognize and classify the objects using the function. The function to classify Artemia cysts and larvae is optimally estimated based on the classification performance using the areas and the plan-form factors of the detected objects. The hatching rate using the image data obtained under the different experimental conditions was estimated in the range of 34-48%. It was shown that the maximum difference is about 19.7% and the average root-mean squared difference is about 10.9% as the difference between the results using an automatic counting (this study) and a manual counting were compared. This technique can be applied to biological specimen analysis using similar imaging information.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.571-574
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• 2005

In this paper, we propose an efficient image segmentation technique for large-sized monochrome images using a hybrid approach which combines threshold and region-based techniques. First, an image is partitioned into fixed-size blocks and for each block the representative intensity is determined by averaging pixel intensities within the block. Next, the neighborhood blocks that have similar characteristics with respect to a specific threshold are merged in order to form candidate regions. Finally, those candidate regions are refined to get final target object regions by merging regions considering the spatial locality and certain criteria. We have performed experiments on images selected from various domains and showed that our technique was able to extract target object regions appropriately from most images.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.868-871
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• 2002

Nowadays, zerotrees based digital watermarking techniques are considered to be an efficient watermarking technique used for multimedia data in a compressed form. This paper presents a technique for watermarking an image, by employing zerotrees derived from the wavelet packet coefficients of the transformed image to carry the watermark signal. By setting a proper threshold in zerotrees determining process, the watermark signal can be recovered without the need of original image. With our proposed technique, more amount of watermark signal can be embedded within the image, compared to ordinary wavelet transform based techniques. The experimental results show the improved performance in both qualities of the resultant watermarked image and robustness of the embedded watermark signal against common signal processing such as brightness/contrast enhancement, high-pass filtering, Gaussian noise adding and JPEG compression scheme