• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2011년도 제43차 동계학술발표논문집 19권1호
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• pp.51-53
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• 2011

최근에는 텍스트정보 보다 동영상정보를 다루는 일이 많아졌고 그에 따라 동영상 데이터의 분할, 색인, 검색 등을 위해 장면 전환 검출이 필요하게 되었다. 장면 전환 검출 기술은 비디오 데이터의 장면 변화가 발생하는 경계를 검출하는 기술이다. 본 논문에서는 에지 이미지를 이용한 장면전환 검출과 이를 위한 임계값 설정, 그리고 결과에서 중복된 이미지와 오 검출 된 이미지를 줄여줄 수 있는 구현에 대하여 실험결과를 바탕으로 설명한다.

• 제어로봇시스템학회논문지
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• 제4권6호
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• pp.759-764
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• 1998

We propose a novel algorithm capable of recognizing the road lane by image processing. Considering the fact that the direction and location of road lane are maintained similarly in successive images we formulate a function to represent the property. However, as noises play the role of making a lot of similar patterns appear and disappear in the road image, keeping of robustness in the lane detection has been known a difficult work. To overcome this problem, we introduce the following three ideas: 1) design of a function based on an edge direction and magnitude, 2) construction of a recursive filter to estimate the function recursively for successive images, 3) principal axis-based line fitting. These concepts enhance the adaptability to cope with the random environment of traffic scene and eventually lead to the reliable detection of a road lane.

• 대한전자공학회논문지
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• 제20권1호
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• pp.7-14
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• 1983

직선 및 곡선과 같은 선형 특징은 영상 처리에 있어 중요한 특징중의 하나이다. 본 논문에서는 의미있는 선형 특징의 새로운 기법이 제안된다. 이 기법은 그래프 이론의 미니멀 스패닝 트리를 이용하여 경계점들을 연결하고 그 다음, 헤어(의미없는 잔가지)와 불합리한 선분을 제거한다. 이와 같이 추적된 선형 특징을 근사화 묘사하기 위하여 부분 선형 근사화를 수행한다. 본 논문에서 제안된 기법으로 실험을 수행하여 그 결과를 보여 주었다.

• 환경영향평가
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• 제10권3호
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• pp.167-174
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• 2001

National Parks in Korea occupy about four percents of South Korean land. This paper aims to prove the potentiality of the application of remotely sensed data for the effective management of National Parks. Different satellite images such as Landsat TM, IRS-1C, Alternative image, and IKONOS image are analyzed for the detection of changes, the extraction of degraded areas, and the comparison of Normalized Difference Vegetation Index (NDVI) in Bukhansan National Park. The artificial structures such as buildings and paved areas are overvalued in relatively higher resolution data. The result showed that the choice of images should be determined according to specific purposes and the combination of different resolution data may be the solution for the effective management of National Park.

• 한국컴퓨터정보학회논문지
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• 제13권6호
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• pp.147-154
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• 2008

본 논문에서는 우선 $X^2$ 히스토그램과 컬러 히스토그램을 합성한 방법과 정규화를 통하여 프레임 간 차이값을 계산한다. 다음으로 거리에 대한 클러스터링과 k-mean 군집화를 이용하여 클러스터의 대표 프레임을 결정한다. 마지막으로 우도비를 이용하여 그룹의 대표 프레임을 결정한다. 제안한 방법은 차이값 계산, 클리스터링과 군집화, 대표 프레임 추출의 3단계 과정을 수행하므로 다른 방법보다 검출이 뛰어나다는 것을 실험을 통해 알 수 있다.

• IEIE Transactions on Smart Processing and Computing
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• 제4권6호
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• pp.403-406
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• 2015

In this paper, we propose a supervoxel clustering-based staircase extraction algorithm to obtain poses and dimensions of staircases from a point cloud. In order to effectively reduce the candidate points and accelerate supervoxel clustering, large planes in the scene, such as walls, floors, and ceilings, are eliminated while scanning the environment. Next, staircase candidates with small planes are initially estimated using supervoxel clustering. Then, parameter values for the staircases are refined, and higher staircases that remain undetected due to occlusion are predicted and generated virtually. Experimental results show that staircases are detected accurately and predicted successfully.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.226-231
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• 1998

This paper describes how a priori road geometry and its estimation may be used to detect road boundaries and lane markings in road scene images. We assume flat road and road boundaries and lane markings are all Bertrand curves which have common principal normal vectors. An active contour is used for the detection of road boundary, and we reconstruct its geometric property and make use of it to detect lane markings. Our approach to detect road boundary is based on minimizing energy function including edge related term and geometric constraint term. Lane position is estimated by pixel intensity statistics along the parallel curve shifted properly from boundary of the road. We will show the validity of our algorithm by processing real road images.

• 전기학회논문지P
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• 제55권2호
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• pp.103-109
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• 2006

In this paper, the detection scheme of the spatial coordinates based on stereo camera for a intelligent path planning of an automatic mobile robot is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity mad obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene. and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation.

• 대한임베디드공학회논문지
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• 제6권1호
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• pp.8-15
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• 2011

This paper presents an effective method for detecting vehicles in front of the camera-assisted car during nighttime driving. The proposed method detects vehicles based on detecting vehicle headlights and taillights using techniques of image segmentation and clustering. First, in order to effectively extract spotlight of interest, a pre-signal-processing process based on camera lens filter and labeling method is applied on road-scene images. Second, to spatial clustering vehicle of detecting lamps, a grouping process use light tracking method and locating vehicle lighting patterns. For simulation, we are implemented through Da-vinci 7437 DSP board with visible light mono-camera and tested it in urban and rural roads. Through the test, classification performances are above 89% of precision rate and 94% of recall rate evaluated on real-time environment.

• Journal of information and communication convergence engineering
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• 제20권3호
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• pp.226-233
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• 2022

Video surveillance is widely used in security surveillance, military navigation, intelligent transportation, etc. Its main research fields are pattern recognition, computer vision and artificial intelligence. This article uses OpenCV to detect and track vehicles, and monitors by establishing an adaptive model on a stationary background. Compared with traditional vehicle detection, it not only has the advantages of low price, convenient installation and maintenance, and wide monitoring range, but also can be used on the road. The intelligent analysis and processing of the scene image using CAMSHIFT tracking algorithm can collect all kinds of traffic flow parameters (including the number of vehicles in a period of time) and the specific position of vehicles at the same time, so as to solve the vehicle offset. It is reliable in operation and has high practical value.