• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.634-640
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• 2018

In this paper, we propose an automatic extraction algorithm of region of interest(ROI) based on medical x-ray images. The proposed algorithm uses segmentation, feature extraction, and reference image matching to detect lesion sites in the input image. The extracted region is searched for matching lesion images in the reference DB, and the matched results are automatically extracted using the Kalman filter based fitness feedback. The proposed algorithm is extracts the contour of the left hand image for extract growth plate based on the left x-ray input image. It creates a candidate region using multi scale Hessian-matrix based sessionization. As a result, the proposed algorithm was able to split rapidly in 0.02 seconds during the ROI segmentation phase, also when extracting ROI based on segmented image 0.53, the reinforcement phase was able to perform very accurate image segmentation in 0.49 seconds.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.2
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• pp.151-157
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• 2002

A 3-dimenstional automatic solder paste inspection system is described that can be used to find defects occurring in solder paste printing process. This system extracts height and volume information very fast as well as area of solder paste printed, using multiple slit ray projection and Galvano-mirror scanning. Methods are presented on calibration of camera and slit projector, real-time image processing of multiple slit images, determination of reference height, and extraction of paste height information are proposed. Performance of the system was successfully demonstrated through field tests.

• Journal of Biomedical Engineering Research
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• v.44 no.5
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• pp.346-353
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• 2023

In this paper, we propose an innovative approach that leverages deep learning to find optimal reference points for achieving precise tooth segmentation in three-dimensional tooth point cloud data. A dataset consisting of 350 aligned maxillary and mandibular cloud data was used as input, and both end coordinates of individual teeth were used as correct answers. A two-dimensional image was created by projecting the rendered point cloud data along the Z-axis, where an image of individual teeth was created using an object detection algorithm. The proposed algorithm is designed by adding various modules to the Unet model that allow effective learning of a narrow range, and detects both end points of the tooth using the generated tooth image. In the evaluation using DSC, Euclid distance, and MAE as indicators, we achieved superior performance compared to other Unet-based models. In future research, we will develop an algorithm to find the reference point of the point cloud by back-projecting the reference point detected in the image in three dimensions, and based on this, we will develop an algorithm to divide the teeth individually in the point cloud through image processing techniques.

• Journal of the Korea Fashion and Costume Design Association
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• v.14 no.1
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• pp.81-96
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• 2012

The purpose of this study is to provide fundamental information for standardization of 3D body measurement. This research analyzes errors occurring in the process of extracting body size from 3D body scan data. First, as a result of analyzing basic state of the 3D body scanner's calibration, the point number of each section was almost the same, while the right and left as well as the front and back coordinates of the center of gravity are not, showing unstable data. Nevertheless, the latter does not influence on the size of cylinder such as width and circumference. Next, we analyzed point coordinates variations of scan data on a mannequin nude by life casting. The result was great deflection in case of complicated or horizontal sections including the reference point beyond proper distance from centers of four cameras. In case of the mannequin's size, accuracy proves comparatively high in that measurement errors in height, width, depth, and length dimension occurred all within allowable errors, only except chest depth, while there were a lot of measurement errors in a circumference dimension. Secondly, analysis of accuracy of automatic extraction identification program algorithm presented that a semi-automatic measurement program is better than an automatic measurement program. While both of them ate very acute in parts related to crotch, they are not in armpit related parts. Therefore, in extracting of human body size from 3D scan data, what really matters seems to parts related to armpits.

• Korean Journal of Remote Sensing
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• v.29 no.5
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• pp.499-508
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• 2013

This article presents a new method for semi-automatic extraction of building information (height, shape, and footprint location) from monoscopic urban scenes. The proposed method is to expand Semi-automatic Volumetric Shadow Analysis (SVSA), which can handle occluded building footprints or shadows semi-automatically. SVSA can extract wrong building information from a single high resolution satellite image because SVSA is influenced by extracted shadow area, image noise and objects around a building. The proposed method can reduce the disadvantage of SVSA by using multi-spectral images. The proposed method applies SVSA to panchromatic and multi-spectral images. Results of SVSA are used as parameters of a cost function. A building height with maximum value of the cost function is determined as actual building height. For performance evaluation, building heights extracted by SVSA and the proposed method from Kompsat-2 images were compared with reference heights extracted from stereo IKONOS. The result of performance evaluation shows the proposed method is a more accurate and stable method than SVSA.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.370-372
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• 2006

본 논문에서 제안하는 방법은 영상에서 중심 객체를 추출하기 위해 에지와 색상 정보에서 추출한 특집 지도와 배경의 영향을 줄이기 위친 창조 지도(reference map)를 제안한 것이 특징이다. 특징 지도는 다른 영역과 현저하게 구분되는 영역을 검출하기 위해서 영상의 특징 값(feature)들을 이용해서 구성한 영상이라고 할 수 있다. 그리고 창조 지도는 배경의 영향을 최소화하면서, 객체가 존재할 확률이 높은 부분을 나타내는 지도이다. 제안하는 방법은 밝기 차 정보를 가지고 있는 에지와 YCbCr 컬러모델과 HSV 컬러모델의 색상 성분을 특징 값으로 사용한다. 이들 특징 값을 이용해서 특징 지도를 구성하는 방법으로 영상 내 색상 차에 의해서 나타나는 경계부분을 구하는 방법을 사용한다. 이 방법을 사용하여 에지 지도와 두 개의 색상 지도의 3가지 특징 지도를 생성한다. 다음으로, 영상 배경의 영향을 줄이기 위해 참조 지도를 구한다. 구해진 참조 지도와 특징 지도들을 이용해서 결합 지도(combination map)를 생성한다. 결함 지도로부터 다각형의 객체 후보 영역을 구하고, 객체 후보 영역에 영상분할을 적용하여 중심 객체를 추출한다. 실험에 사용된 영상들은 Corel DB를 사용하였으며, 실험결과로써 precision은 84.3%, recall은 81.3%의 성능을 보인다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.263-271
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• 2016

Software requirement analysis is necessary for successful software development project. Specially, incomplete requirement is the most influential causes of software project failure. Incomplete requirement can bring late delay and over budget because of the misunderstanding and ambiguous criteria for project validation. Software requirement patterns can help writing more complete requirement. These can be a reference model and standards when author writing or validating software requirement. Furthermore, when a novice writes the software scenario, the requirement patterns can be one of the guideline. In this paper proposes an automatic approach to identifying software scenario patterns from various software scenarios. In this paper, we gathered 83 scenarios from eight industrial systems, and show how to extract 54 scenario patterns and how to find omitted action of the scenario using extracted patterns for the feasibility of the approach.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.1141-1144
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• 2005

In this paper, we propose an automatic displacement system for testing stability of structure. Photogrammetry is a method which can measure accurate 3D data from 2D images taken from different locations and which is suitable for analyzing and measuring the displacement of structure. This paper consists of camera calibration, feature extraction using coded target & retro-reflective circle, 3D reconstruction and analyzing accuracy. Multi-view camera which is used for measuring displacement of structure is placed with different location respectively. Camera calibration calculates trifocal tensor from corresponding points in images, from which Euclidean camera is calculated. Especially, in a step of feature extraction, we utilize sub-pixel method and pattern recognition in order to measure the accurate 3D locations. Scale bar is used as reference to measure. the accurate value of world coordinate..

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.203-211
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• 2005

In this paper, we propose a new automatic fingerprint identification system that identifies individuals in large databases. The algorithm consists of three steps; preprocessing, classification, and matching, in the classification. we present a new classification technique based on the statistical approach for directional image distribution. In matching, we also describe improved minutiae candidate pair extraction algorithm that is faster and more accurate than existing algorithm. In matching stage, we extract fingerprint minutiaes from its thinned image for accuracy, and introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection in comparison stage of two fingerprints quickly. This algorithm is invariant to translation and rotation of fingerprint. The proposed system was tested on 1000 fingerprint images from the semiconductor chip style scanner. Experimental results reveal false acceptance rate is decreased and genuine acceptance rate is increased than existing method.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.815-822
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• 2003

Fingerprint image enhancement and minutiae matching are two key steps in an automatic fingerprint identification system. In this paper, we propose a fingerprint recognition technique by using minutiae linking information. Recognition process have three steps ; preprocessing, minutiae extraction, matching step based on minutiae pairing. After extracting minutiae of a fingerprint from its thinned image for accuracy, we introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection with low cost in comparison stage of two fingerprints. This algorithm is invariable to translation and rotation of fingerprint. The matching algorithm was tested on 500 images from the semiconductor chip style scanner, experimental result revealed the false acceptance rate is decreased and genuine acceptance rate is increased than existing method.