• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.923-933
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• 2007

In this paper, we present a method for performance enhancement of the marker detection system by using SVM(Support Vector Machine) and LDA(Linear Discriminant Analysis). It converts the input image to a binary image and extracts contours of objects in the binary image. After that, it approximates the contours to a list of line segments. It finds quadrangle by using geometrical features which are extracted from the approximated line segments. It normalizes the shape of extracted quadrangle into exact squares by using the warping technique and scale transformation. It extracts feature vectors from the square image by using principal component analysis. It then checks if the square image is a marker image or a non-marker image by using a SVM classifier. After that, it computes feature vectors by using LDA for the extracted marker images. And it calculates the distance between feature vector of input marker image and those of standard markers. Finally, it recognizes the marker by using minimum distance method. Experimental results show that the proposed method achieves enhancement of recognition rate with smaller feature vectors by using LDA and it can decrease false detection errors by using SVM.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.10a
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• pp.175-175
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• 2003

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.130-132
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• 2012

The use of visual media has been increased by development of contemporary society. To use these information of image, there are various methods of image processing. Edge detection which is one of those is technique to detect dramatically changing part of image brightness. Existing methods detect edge through mask which is composited by constant values. Because existing methods do not consider factor as location, direction of pixel in image, performance of edge detecting in insufficient. Therefore, an algorithm which is using variable vector for the variation of brightness in mask of $3{\times}3$ pixels is proposed.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1226-1232
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• 2010

A door can serve as a feature for place classification and localization for navigation of a mobile robot in indoor environments. This paper proposes a door detection method based on the recognition of various door handles using the general Hough transform (GHT) and support vector machine (SVM). The contour and color histogram of a door handle extracted from the database are used in GHT and SVM, respectively. The door recognition scheme consists of four steps. The first step determines the region of interest (ROI) images defined by the color information and the environment around the door handle for stable recognition. In the second step, the door handle is recognized using the GHT method from the ROI image and the image patches are extracted from the position of the recognized door handle. In the third step, the extracted patch is classified whether it is the image patch of a door handle or not using the SVM classifier. The door position is probabilistically determined by the recognized door handle. Experimental results show that the proposed method can recognize various door handles and detect doors in a robust manner.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.2
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• pp.181-189
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• 2002

In this paper, we designed and implemented Avata construction system using XML(extensible Markup Language) and SVG(Scalable Vector Graphic). The Web character created with Avata(or Web character) construction system are displayed in same (on without damage of image, regardless terminal type and user can modify and change image easily in form that want. Compare with existing Web character system, the Reusability of web character part element Is increased greatly with Avata construction system of this paper. Because SVG is described by text, graphic retrieval is convenient, and applications can use easily SVG document. Also, SVG can create web graphic document dynamically with database because can access easily in all graphic primitives of line, Polygon, text, image etc. As well as web character using study finding, we may develop usable technology to some contents on World Wide Web.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.154-154
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• 2021

Since the development of Bubble Image Velocimetry (BIV) technique as the complementary technique of Particle Image Velocimetry (PIV), the application of digital imaging technique in the field of hydraulic and coastal engineering increased rapidly. BIV works very well in multi-phase flow (air-water) flows where the PIV technique doesn't. However, the velocity field obtained from BIV technique often resulted in a velocity vector on the outside of the flow (false velocity) since the Field of View (FOV) usually not only cover the air-water flow but also the area outside the flow. In this study, a simple technique of post processing velocity field was developed. This technique works based on the average of the pixel value in the interrogation area. An image of multi-phase flow of wave overtopping was obtained through physical experiment using BIV technique. The velocity calculation was performed based on the similar method in PIV. A velocity masking technique developed in this study then applied to remove the false velocity vector. Result from non-masking, manually removed and auto removed false velocity vector were presented. The masking technique show a similar result as manually removed velocity vector. This method could apply in a large number of velocity field which is could increase the velocity map post-processing time.

• Journal of the Korea Computer Industry Society
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• v.2 no.8
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• pp.1075-1088
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• 2001

In this paper, we propose a method for dynamic selection of unrestricted motion vector(UMV) or default prediction mode(DPM) in H.263 bit stream. For this, we use the error of compensated image and the magnitude of motion vector. In the proposed strategy, the UMV mode is dynamically applied in a frame according to average magnitude of motion vector and error of compensated image. This scheme has improved the quality of image compared to the fixed mode UMV or DPM only. Number of searching points are greatly reduced when comparing to UMV The proposed method is more profitable to long video sequences having camera movement locally.

• Journal of the Korea Computer Industry Society
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• v.2 no.7
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• pp.997-1014
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• 2001

In this paper, we propose a method for dynamic selection of unrestricted motion vector(UMV) or default prediction mode(DPM) in H.263 bit stream. For this, we use the error of compensated image and the magnitude of motion vector. In the proposed strategy, the UMV mode is dynamically applied in a frame according to average magnitude of motion vector and error of compensated image. This scheme has improved the quality of image compared to the fixed mode UMV or DPM only. Number of searching points are greatly reduced when comparing to UMV. The Proposed method is more profitable to long video sequences having camera movement locally.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.79-86
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• 2006

Classification technology is essential for fast retrieval in large multi-media database. This paper proposes a combining GA(Genetic Algorithm) and SVM(Support Vector Machine) model to fast retrieval. We used color and texture as feature vectors. We improved the retrieval accuracy by using proposed model which retrieves an optimal feature vector set in extracted feature vector sets. The first performance test was executed for the performance of color, texture and the feature vector combined with color and texture. The second performance test, was executed for performance of SVM and proposed algorithm. The results of the experiment, using the feature vector combined color and texture showed a good Performance than a single feature vector and the proposed algorithm using hybrid method also showed a good performance than SVM algorithm.

• Journal of Korea Multimedia Society
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• v.16 no.9
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• pp.1057-1066
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• 2013

Personal verification using finger-knuckle-print(FKP) uses lines and creases at the finger-knuckle area, so the orientation information of texture is an important feature. In this paper, we propose an effective FKP verification method which extracts keypoints using SIFT algorithm and matches the keypoints by vector similarity. The vector is defined as a direction vector which connects a keypoint extracted from a query image and a corresponding keypoint extracted from a reference image. Since the direction vector is created by a pair of local keypoints, the direction vector itself represents only a local feature. However, it has an advantage of expanding a local feature to a global feature by comparing the vector similarity among vectors in two images. The experimental results show that the proposed method is superior to the previous methods based on orientation codes.