• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.224-230
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• 2013

Lane boundary detection plays a key role in the driver assistance system. This study proposes a robust method for detecting lane boundary in severe environment. First, a horizontal line detects form the original image using improved Vertical Mean Distribution Method (iVMD) and the sub-region image which is under the horizontal line, is determined. Second, we extract the lane marking from the sub-region image using Canny edge detector. Finally, K-means clustering algorithm classifi left and right lane cluster under variant illumination, cracked road, complex lane marking and passing traffic. Experimental results show that the proposed method satisfie the real-time and efficient requirement of the intelligent transportation system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.893-898
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• 2013

It is always a dream to recreate the experience of a particular place, the Panorama Virtual Reality has been interpreted as a kind of technology to create virtual environments and the ability to maneuver angle for and select the path of view in a dynamic scene. In this paper we examined an efficient method for Image registration and stitching of captured imaged. Two approaches are studied in this paper. First, dynamic programming is used to spot the ideal key points, match these points to merge adjacent images together, later image blending is used for smooth color transitions. In second approach, FAST and SURF detection are used to find distinct features in the images and nearest neighbor algorithm is used to match corresponding features, estimate homography with matched key points using RANSAC. The paper also covers the automatically choosing (recognizing, comparing) images to stitching method.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.2
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• pp.17-24
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• 2014

This paper proposes an automatic extraction method of control point based on Geospatial Web Service. The proposed method consists of 3 steps. 1) The first step is to acquires reference data using the Geospatial Web Service. 2) The second step is to finds candidate control points in reference data and the target image by SURF algorithm. 3) By using RANSAC algorithm, the final step is to filters the correct matching points of candidate control points as final control points. By using the Geospatial Web Service, the proposed method increases operation convenience, and has the more extensible because of following the OGC Standard. The proposed method has been tested for SPOT-1, SPOT-5, IKONOS satellite images and has been used military standard data as reference data. The proposed method yielded a uniform accuracy under RMSE 5 pixel. The experimental results proved the capabilities of continuous improvement in accuracy depending on the resolution of target image, and showed the full potential of the proposed method for military purpose.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.513-516
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• 2011

기존의 실시간 파노라마 합성 알고리즘에서는 매칭점과 입력 영상에서의 outlier를 구분하고 제거하기가 어렵기 때문에 노이즈가 많은 영상 또는 반복적인 패턴이 많은 영상에서 왜곡이 쉽게 발생하는 문제가 있다. 따라서 본 논문에서는 기존의 실시간 파노라마 합성 프레임웍에서 실시간 합성 조건을 만족시키면서 효과적으로 매칭점과 입력 영상에서의 outlier를 제거하는 방법을 제안한다. 이를 위해서 선형 모델에서 outlier을 제거하는 데 주로 사용되는 RANSAC 알고리즘을 실시간 파노라마 합성에서 사용되는 비선형 모델에 적용 가능하도록 수정하고 속도 향상을 위해서 사용되는 모델의 파라미터를 줄이는 방법을 제안한다. 이를 통하여 매칭점 중에 존재하는 outiler를 제거하고 전체 매칭점 중에서 inlier 비율을 이용하여 입력되는 영상시퀀스에서 outlier 영상을 제거하는 방법을 제안한다. 실험 결과 기존의 방법에 비해서 합성 결과의 왜곡이 줄어드는 것을 확인하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.242-244
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• 2014

파노라마 영상은 하나의 영상이 가지는 제한된 시점의 한계를 극복하고 폭넓은 시야를 가질 수 있다는 점에서 최근 여러 분야에서 활용되고 있는 기술이다. 본 논문에서는 자연스러운 파노라마 영상 생성을 위해 SURF(speed up robust feature)를 이용한 특징점 기반의 파노라마 영상 생성 기법을 제안한다. SURF 알고리즘을 사용하면 정합할 두 영상에서 특징점들을 추출할 수 있다. 추출된 특징점들을 RANSAC(random sample consensus) 알고리즘을 통해 특징점 간 정합시 오차율을 최소화한다. 또한, 이미지 왜곡을 최소화하기 위해 실린더 투영을 이용하여 영상을 보정한다. 최종적으로, 서로 다른 두 영상을 합성할 때 발생하는 경계 주변의 이질감을 보완하기 위해 블렌딩 기법을 사용함으로써 자연스러운 파노라마 영상을 생성한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.7
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• pp.685-692
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• 2016

In this paper, we not only take advantage of the SIFT features in banknote recognition, which has robustness to illumination changes, geometric rotation as well as scale changes, but also propose the hierarchical banknote recognition algorithm, which comprised of feature vector extraction from the frame grabbed image of the banknotes, and matching to the prepared data base of multinational banknotes by ANN algorithm. The images of banknote under the developed UV, IR and white illumination are used so as to extract the SIFT features peculiar to each banknotes. These SIFT features are used in recognition of the nationality as well as face value. We confirmed successful function of the proposed algorithm by applying the proposed algorithm to the banknotes of Korean and USD as well as EURO.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.473-480
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• 2007

Feature tracking in video frame sequences has suffered from the instability and the frequent failure of feature matching between two successive frames. In this paper, we propose a robust 2D feature tracking method that is stable to long video sequences. To improve the stability of feature tracking, we predict the spatial movement in the current image frame using the state variables. The predicted current movement is used for the initialization of the search window. By computing the feature similarities in the search window, we refine the current feature positions. Then, the current feature states are updated. This tracking process is repeated for each input frame. To reduce false matches, the outlier rejection stage is also introduced. Experimental results from real video sequences showed that the proposed method performs stable feature tracking for long frame sequences.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.116-123
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• 2009

Feature point matching, which is finding the corresponding points from two images with different viewpoint, has been used in various vision-based applications and the demand for the real-time operation of the matching is increasing these days. This paper presents a real-time feature point matching method by using a local descriptor derived by Zernike moments. From an input image, we find a set of feature points by using an existing fast corner detection algorithm and compute a local descriptor derived by Zernike moments at each feature point. The local descriptor based on Zernike moments represents the properties of the image patch around the feature points efficiently and is robust to rotation and illumination changes. In order to speed up the computation of Zernike moments, we compute the Zernike basis functions with fixed size in advance and store them in lookup tables. The initial matching results are acquired by an Approximate Nearest Neighbor (ANN) method and false matchings are eliminated by a RANSAC algorithm. In the experiments we confirmed that the proposed method matches the feature points in images with various transformations in real-time and outperforms existing methods.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.481-487
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• 2023

Recently, interest in UAM (Urban Air Mobility) has surged as a critical solution to urban traffic congestion and air pollution issues. However, efficient UAM operation requires accurate 3D Point Cloud data processing, particularly in separating the ground and objects. This paper proposes and validates a method for effectively separating ground and objects in a UAM environment, taking into account its dynamic and complex characteristics. Our approach combines attitude information from MEMS sensors with ground plane estimation using RANSAC, allowing for ground/object separation that isless affected by GPS errors. Simulation results demonstrate that this method effectively operates in UAM settings, marking a significant step toward enhancing safety and efficiency in urban air mobility. Future research will focus on improving the accuracy of this algorithm, evaluating its performance in various UAM scenarios, and proceeding with actual drone tests.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1448-1451
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• 2012

파노라마 가상현실이란 특정 장소의 경험을 재현하는 방식으로, 현실 세계의 장소에 직접 가보지 않고 가상 현실 속의 사물이나 정보를 보다 쉽고 빠르게 탐색하고 습득 할 수 있다. 본 논문에서는, 우리는 이상적인 키 포인트를 탐지하는 동적 프로그래밍을 사용하여 함께 이 지점과 인접한 이미지를 병합하고, 부드러운 색상 전환을 위해 이미지를 혼합하는데 사용된다. FAST와 SURF 탐지는 이미지의 확실한 특징을 찾는데 사용되고, 가장 가까운 이웃 알고리즘은 해당되는 특징을 일치시키는데 사용되며, RANSAC을 사용하여 일치하는 키 포인트를 homography로 판단한다. 이러한 방법으로 이미지를 자동 선택하여 스티칭하는 방법을 사용한다.