• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.55-57
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• 2014

본 논문에서는 자동차 번호판 인식을 위해 직선검출법, 모폴로지에 의한 검출법을 사용하지 않고, Blob 레이블링 기법을 이용한 번호판 인식 기법을 제안한다. 고성능 컴퓨팅 시스템의 성능 향상을 위한 효율적인 동적 작업부하 균등화 정책을 제안한다. ITS분야에서 가장 중요한 요소라 할 수 있는 자동차 번호판 인식은 자동화된 차량 관리 시스템 구성에 필수적인 요소로 요구된다. 또한, 자동차와 관련된 정보는 직, 간접적으로 높은 중요도를 가지고 있으며, 자동차와 관련된 정보가 이용되는 영역은 교통관리, 교통량분석, 자동 요금 징수 시스템, 자동차 위법 단속 등 응용범위가 나날이 넓어지고 있다. 본 논문에서는 자동차 번호판 인식을 위해 Blob 레이블링 기법을 이용하였으며, 번호판 인식을 위한 영상 샘플은 오츠알고리즘을 이용하여 이진화된 영상을 사용하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.8
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• pp.1495-1504
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• 2008

New license plates have been used since 2007. This paper proposes a new license plate extraction method using a gray labeling and a fuzzy reasoning method. First, the proposed method extracts the candidate plates by the gray labeling which is the enhanced version of a non-recursive flood-filling algorithm. By newly designed fuzzy inference system. fitness of each candidate plates are calculated. Finally, the area of the license plate in a image is extracted as a region of the candidate label which has the highest fitness. In the experiments, various license plate images took from indoor/outdoor parking lot, street, etc. by digital camera or cellular phone were used and the proposed extraction method was showed remarkable results of a 94 percent success.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.3
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• pp.151-157
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• 2009

In this paper, we proposed an algorithm of redeye correction. For naturally redeye correction, we assumed positions of the redeye at an image which produced redeye, and we estimated rate of the redeye to apply the appropriate redeye correction suitably. We extract and label pixels those are possible of generating redeye using red, skin and reflected light color. The each labeled group is decided by rates of length and width, dimension, density, the color of white of the eye and reflected light color of groups for the redeye group. We corrected positions of redeye using blurring effect, naturally. In the case of designing the proposed algorithm, we designed the redeye correction hardware using the minimum of memories for efficiency of hardware.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.359-365
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• 2011

This study aims at filtering ALS points into ground and non-ground effectively through labeling and window based algorithm by utilizing 2D adjacency based on scan line. Firstly, points adjacency is constructed through minimal search based on scan line. Connected component labeling algorithm is applied to classify raw ALS points into ground and non-ground by utilizing the adjacency structure. Then, some small objects are removed by morphology filtering, and isolated ground points are restored by IDW estimation. The experimental results shows that the method provides good filtering performance( about 97% accuracy) for diverse sites, and the overall processing takes less time than converting raw data into TIN or raster grid.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.11
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• pp.634-639
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• 2002

A Shortest Path Algorithm is the method to find the most efficient route among many routes from a start node to an end node. It is based on Labeling methods. In Labeling methods, there are Label-Setting method and Label-Correcting method. Label-Setting method is known as the fastest one among One-to-One shortest path algorithms. But Benjamin[1,2] shows Label-Correcting method is faster than Label-Setting method by the experiments using large road data. Since Graph Growth algorithm which is based on Label-Correcting method is made to find One-to-All shortest path, it is not suitable to find One-to-One shortest path. In this paper, we propose a new One-to-One shortest path algorithm. We show that our algorithm is faster than Graph Growth algorithm by extensive experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1355-1360
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• 2020

In a map, placing the labels, corresponding to names or explanations of specific features, is called map labeling. In this paper, n points on a line are given, and placing rectangular labels for the points is considered. Particularly, the labels have a same height and their lower sides lie on a straight line in the upper of the line on which the given points are. The points and the labels are connected by polygonal lines, which are called leader lines. The leader lines are classified into straight leader lines and bended leader lines, where the straight leader line consists of only the vertical line and the bended leader line consists of vertical, horizontal, vertical lines. The problem is placing the labels to minimize the number of bended leader lines, and we propose an O(nlogn)-time algorithm, which improves the O(n2)-time algorithm previously provided in [13].

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.835-843
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• 2023

Given the structure of XML data, path and tree pattern matching algorithms play an important role in XML query processing. To facilitate decisions or relationships between nodes, nodes in an XML tree are typically labeled in a way that can quickly establish an ancestor-descendant on relationship between two nodes. However, these techniques have the disadvantage of re-labeling existing nodes or recalculating certain values if insertion occurs due to sequential updates. Therefore, in current labeling techniques, the cost of updating labels is very high. In this paper, we propose a new labeling technique called Fast XML encoding, which supports the update of order-sensitive XML documents without re-labeling or recalculation. It also controls the length of the label by reusing deleted labels at the same location in the XML tree. The proposed reuse algorithm can reduce the length of the label when all deleted labels are inserted in the same location. The proposed technique in the experimental results can efficiently handle order-sensitive queries and updates.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.5
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• pp.35-49
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• 2014

This paper proposes the on-road object detection and classification algorithm by using a detection system consisting of only laser scanners. Each sensor data acquired by the laser scanner is fused with a grid map and the measurement error and spot spaces are corrected using a labeling method and dilation operation. Fuzzy method which uses the object information (length, width) as input parameters can classify the objects such as a pedestrian, bicycle and vehicle. In this way, the accuracy of the detection system is increased. Through experiments for some scenarios in the real road environment, the performance of the proposed detection and classification system for the actual objects is demonstrated through the comparison with the actual information acquired by GPS-RTK.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.245-248
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• 2003

볼륨데이터에서 관심대상의 특징을 추출하기 위해서 3D레이블링을 3차원 세포영상의 분석에 적합한 레이블링 방법인 SIL(slice Information base labeling)을 제안하였다. SIL은 각 슬라이스 정보를 이용하여 레이블링을 수행하므로 영상의 특징에 안는 레이블링으로의 확장이 유용하고 메모리 효율이 높다. 몇 개의 실험 영상으로 다른 방법과 비교한 결과 성능면에서도 우수 결과를 얻었다. 또한 레이블링을 통해서 얻어진 피쳐값으로 세포 영상을 분석하였으며, 콘포컬 현미경 영상을 이용하였을때 실험영상에서 결과를 추출하는데 걸린 시간은 SIL방법이 기존 방법보다 2배 가량 빨랐다. 다양한 3차원 에이블링 방법 중 적용되는 영상에 따라 각기 다른 결과를 얻었지만,3차원 세포영상의 분석에는 SIL 방법이 우수하다는 결론을 얻었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.223-226
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• 2011

본 논문은 웹 카메라로부터 입력받은 영상을 이용하여 손 영역을 추출하여 마우스를 대체할 수 있는 핸드마우스를 구현한다. 먼저 웹 카메라를 이용하여 입력받은 영상에서 손 영역을 추출한다. 손영역을 추출하기 위해서 HSV 컬러 모델에서 조도 변화에 강인한 Hue값과 피부색 특징이 잘 나타나는 YcbCr 컬러 공간을 이용하여 손 후보 영역을 획득한다. 손 후보 영역에서 레이블링(labeling) 알고리즘을 적용하여 정확한 손 영역을 추출한다. 추출한 손 영역에서 무게 중심점을 구한 후, 무게 중심점으로부터 거리를 이용하여 손 영역을 분리한다. 분리된 손 영역에서 무게 중심점으로부터 거리 정보를 이용하여 손 영역의 최종 특징 점을 추출한다. 본 논문에서 제안한 방법은 추출한 손 모양의 손끝 정보를 이용하여 마우스 이벤트를 수행함으로써 사용자가 사용하기 편리한 핸드마우스를 구현하였다.