• Journal of the Korean Graphic Arts Communication Society
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• v.8 no.1
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• pp.71-87
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• 1990

This paper presents a simple algorithm to obtain three dimensional information of an object. In the preprocessing of the stereo matching,feature point informations of stero image must be less sensitive to noise and well liked the correspondance problem. This paper described a simple technique of struture feature extraction of 3-D object and used edge-end point expanding method for unconnected line instade of Hough transform. The feature such as corner point and their angles are used for matching problem. The experimental results show that the described algorithm is a useful method for stereo correspondence problem.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2002.04a
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• pp.154-158
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• 2002

The object of this study is to find out our present exterior color palette of the apartment buildings by Han River, which represents the visual image of Seoul, to reveal how well it is harmonized with its surroundings along with the last 10 years researches, and to compare its correspondence with the city plan of Seoul. Furthermore, it is the ultimate purpose to prepare source materials for desirable color plan of the city.

• Journal of the Optical Society of Korea
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• v.5 no.3
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• pp.90-92
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• 2001

Direct and inverse mathematical operators of stereo transformation (stereo operators) are studied in this paper. The stereo operators install a one-to-one correspondence between three dimensional coordinates of any point in space and the stereo coordinates which can be displayed on the screen under the given conditions, i.e. stereo vision base and the position of viewer. The stereo operators can be applied to the analyses of stereoscopic image distortions when the stereo vision base and the position of viewer are changed.

• Journal of Biomedical Engineering Research
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• v.20 no.2
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• pp.155-164
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• 1999

In this paper, the prototype of SIS(Simulated Implantation System) for human femoral head is introduced. SIS is a software which carries on a virtual femoral head replacement surgery including 3d visualization as well as various numeric analyses between a patient's femur and artificial femur through certain stages of the image processing and of the computer graphics. Also, processes required after acquiring consecutive CT-images and projected image of an artificial femur are discussed, and the corresponding results including prototype of SIS are given.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.277-286
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• 2009

Image registration is a process to establish the spatial correspondence between images of the same scene, which are acquired at different view points, at different times, or by different sensors. In this paper, we introduce a robust brain registration technique for correcting the difference between two temporal images by the different coordinate systems in MR and CT image obtained from the same patient. Two images are registered where this measure is minimized using a modified conditional entropy(MCE: Modified Conditional Entropy) computed from the joint histograms for the intensities of two given images, we conduct the rendering for visualization of 3D volume image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1597-1610
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• 2022

At present, the main method of high-speed train chassis detection is using computer vision technology to extract keypoints from two related chassis images firstly, then matching these keypoints to find the pixel-level correspondence between these two images, finally, detection and other steps are performed. The quality and accuracy of image matching are very important for subsequent defect detection. Current traditional matching methods are difficult to meet the actual requirements for the generalization of complex scenes such as weather, illumination, and seasonal changes. Therefore, it is of great significance to study the high-speed train image matching method based on deep learning. This paper establishes a high-speed train chassis image matching dataset, including random perspective changes and optical distortion, to simulate the changes in the actual working environment of the high-speed rail system as much as possible. This work designs a convolutional neural network to intensively extract keypoints, so as to alleviate the problems of current methods. With multi-level features, on the one hand, the network restores low-level details, thereby improving the localization accuracy of keypoints, on the other hand, the network can generate robust keypoint descriptors. Detailed experiments show the huge improvement of the proposed network over traditional methods.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.37-48
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• 2012

Image registration is a process to establish the spatial correspondence between the images of same scene, which are acquired at different view points, at different times, or by different sensors. In this paper, we propose an effective registration method for images acquired by multi-sensors, such as EO (electro-optic) and IR (infrared) sensors. Image registration is achieved by extracting features and finding the correspondence between features in each input images. In the recent research, the multi-sensor image registration method that finds corresponding features by exploiting NMI (Normalized Mutual Information) was proposed. Conventional NMI-based image registration methods assume that the statistical correlation between two images should be global, however images from EO and IR sensors often cannot satisfy this assumption. Therefore the registration performance of conventional method may not be sufficient for some practical applications because of the low accuracy of corresponding feature points. The proposed method improves the accuracy of corresponding feature points by combining the gradient orientation as spatial information along with NMI attributes and provides more accurate and robust registration performance. Representative experimental results prove the effectiveness of the proposed method.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.305-310
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• 2010

In this paper, we propose a heuristic algorithm for motion correspondence based on a point series similarity. A point series is a sequence of points which are sorted in the ascending order of their x-coordinate values. The proposed algorithm clusters the points of a previous frame based on their local adjacency. For each group, we construct several potential point series by permuting the points in it, each of which is compared to the point series of the following frame in order to match the set of points through their similarity based on a proximity constraint. The longest common subsequence between two point series is used as global information to resolve the local ambiguity. Experimental results show an accuracy of more than 90% on two image sequences from the PETS 2009 and the CAVIAR data sets.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.8
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• pp.1001-1010
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• 1998

The purpose of this study was to investigate the images and characteristic formative elements of Korean traditional patterns. The Korean pattern image could be interpreted into visual elements of design based on the images, the characteristic formative elements of Korean traditional patterns, and their relationships. Fourteen patterns selected from 5 groups of Korean patterns were used as stimuli. An image evaluation using a 2-point sementica scale of 19 bipolar adjectives, and an impression evaluation of which results were presented by visual drawing using lines and shapes were carried out. The data were analyzed by correspondence analysis and cluster analysis. The major findings are as follows; 1. Fourteen patterns and 19 adjectives were marked on a perception map composed of two (x and y-) axes. The bipoles of x- and y axes were soft-hard and splendid-artless, respectively. 2. Four clusters semerged to account for the dimensional sturucture of 14 patterns and 19 adjectives. These were splendid image, soft image, individualistic image, and sophisticated image. However there was no pattern which belonged to the cluster, sophisticated image. The Korean pattern image was founded to be better related to the kind of patterns than the type of patterns. 3. The characteristic formative elements obtained from the impression test were contour of motif, repeated line or shape, various curved lines, and decorative elements. 4. The splendid image was related to Bongwhang patterns and detailed line and complexity. The individualistic image was related to the abstractive form of Bongwhang pattern and the decorative form of Cloud pattern both of which have the characteristics of point-symmetry and abstraction, and Turtle-back pattern. In this case, the related charac-teristic formative element was identified to be repeated lines. The soft image was related to Moran, Cloud, and Taegeuk patterns. The related characteristic elements were various types of curved lines, decorative elements, and rounded contours.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.1 s.307
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• pp.27-34
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• 2006

In this paper, we propose a combined region-based image retrieval system using EHD(Edge Histogram Descriptor) and CLD(Color Layout Descriptor) of MPEG-7 descriptors. The combined descriptor can efficiently describe edge and color features in terms of sub-image regions. That is, the basic unit for the selection of the region-of-interest (ROI) in the image is the sub-image block of the EHD, which corresponds to 16 (i.e., $4{\times}4)$ non-overlapping image blocks in the image space. This implies that, to have a one-to-one region correspondence between ELE and CLD, we need to take an $8{\times}8$ inverse DCT (IDCT) for the CLD. Experimental results show that the proposed retrieval scheme can be used for image retrieval with the ROI based image retrieval for MPEG-7 indexed images.