• Annual Conference of KIPS
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• 2006.11a
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• pp.19-22
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• 2006

In this paper we present a vision based place recognition method which uses Bayesian method with feed back of image retrieval. Both Bayesian method and image retrieval method are based on interest features that are invariant to many image transformations. The interest features are detected using Harris-Laplacian detector and then descriptors are generated from the image patches centered at the features' position in the same manner of SIFT. The Bayesian method contains two stages: learning and recognition. The image retrieval result is fed back to the Bayesian recognition to achieve robust and confidence. The experimental results show the effectiveness of our method.

• Journal of the Korean Society for Nondestructive Testing
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• v.12 no.4
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• pp.18-25
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• 1993

This paper is to aim the microdefect evaluation of If package into a quantitative from NDI's image processing of ultrasonic wave. (1) Automatically repeated discrimination analysis method can be devided in the category of all kind of defects on IC package, and also can be possible to have a sampling of partial delamination. (2) It is possible that the information of edge section in silicon chip surrounding can be extractor by the partial image processing of IC package. Also, the crack detection is possible between the resin part and lead frame.

• Journal of the Korean Vacuum Society
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• v.6 no.S1
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• pp.66-69
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• 1997

Porosity is one important characteristic feature and structural index of sprayed coatings. A method of measurement of porosity, EPMA-EDS image processing is developed in the paper. The characteristics of pores can be determined by processing of the image obtained from an electron microscope via VISTA, Not only the porosity can be presented but also the statistical result of pore size distribution. Finally it can be drawn from this paper that EPMA-EDS is a quite effective method to completely characterize the pores in plasma sprayed coatings.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10b
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• pp.1303-1308
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• 2000

Detection of square shape voids with size 30$\times$20$\times$5cm and 20$\times$20$\times$20cm in concrete were carried out by ultrasonic image processing technique. The advantages and limitations of this technique for non-destructive inspection of square shape voids in concrete are investigated. In this study, it has been verified that the semi-direct measurement method is more effective than the other methods for detecting the voids in concrete using ultrasonic image processing method.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.117-122
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• 2002

Electrical discharge machining uses thermal energy from electrical discharge, while wire electrical discharge machining (WEDM) technology is widely used in conductive material machining. This paper proposes a method for evaluating the characteristics of wires in WEDM. In order to evaluate the wire processing performance, processing speed and roughness, straightness, corner processing have been assessed with precision experiment equipment and image processing including Laplacian filtering with various threshold levels.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.715-716
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• 2013

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.370-384
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• 2017

The image segmentation is the most important operation in an image processing system. It is located at the joint between the processing and analysis of the images. Unsupervised segmentation aims to automatically separate the image into natural clusters. However, because of its complexity several methods have been proposed, specifically methods of optimization. In our work we are interested to the technique SFLA (Shuffled Frog-Leaping Algorithm). It's a memetic meta-heuristic algorithm that is based on frog populations in nature searching for food. This paper proposes a new approach of unsupervised image segmentation based on SFLA method. It is implemented and applied to different types of images. To validate the performances of our approach, we performed experiments which were compared to the method of K-means.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.175-181
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• 2005

This paper describes the development of on-line computer vision laboratories to teach the detailed image processing and pattern recognition techniques. The computer vision laboratories include distant image acquisition method, basic image processing and pattern recognition methods, lens and light, and communication. This study introduces a case study that teaches computer vision in distance learning environment. It shows a schematic of a distant loaming workstation and contents of laboratories with image processing examples. The study focus more on the contents of the vision Labs rather than internet application method. The study proposes the ways to improve the on-line computer vision laboratories and includes the further research perspectives

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.6
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• pp.345-352
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• 2014

Edge detection considers the important technical details of digital image processing. Many edge detection operators already perform edge detection in digital color imaging. In this study, the edge of many real color images that represent the type of digital image was detected using a new operator in the least square approximation method, which is a type of numerical method. The Linear Fitting algorithm is computationally more expensive compared to the Canny, LoG, Sobel, Prewitt, HIS, Fuzzy, Parametric, Synthetic and Vector methods, and Robert' operators. The results showed that the new method can detect an edge in a digital color image with high efficiency compared to standard methods used for edge detection. In addition, the suggested operator is very useful for detecting the edge in a digital color image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4375-4388
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• 2018

To solve the problem of transmission errors in stereoscopic images, this paper proposes a novel error concealment (EC) method using superpixel segmentation and adaptive disparity selection (SSADS). Our algorithm consists of two steps. The first step is disparity estimation for each pixel in a reference image. In this step, the numbers of superpixel segmentation labels of stereoscopic images are used as a new constraint for disparity matching to reduce the effect of mismatching. The second step is disparity selection for a lost block. In this step, a strategy based on boundary smoothness is proposed to adaptively select the optimal disparity which is used for error concealment. Experimental results demonstrate that compared with other methods, the proposed method has significant advantages in both objective and subjective quality assessment.