• 정보처리학회논문지B
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• 제19B권2호
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• pp.113-122
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• 2012

스테레오 정합(stereo matching) 기술은 주어진 두 영상에서 동일한 물체의 영상점이 어떤 위치 관계를 가지고 있는지를 결정하는 기술이다. 본 논문에서는 영상 특징점에 대해 스테레오 위치관계를 결정하는 새로운 스테레오 특징점 정합(stereo feature matching) 방법을 제시한다. 제안하는 방법은 주어진 스테레오 영상에서 FAST 추출기를 이용하여 특징점을 추출하고, 특징점 벡터들의 정보들을 내부에 포함하는 특징창(feature window)이라는 공간을 정의하여 스테레오 정합의 성능을 향상한다. 제안하는 방법은 표준 영상에 추출된 특징점들에 대해 특징창을 생성하고, 참조 영상에서 표준 영상의 특징창과 가장 유사한 특징창을 탐색 및 결정한 다음, 결정된 두 개의 특징창 내부의 특징점들의 시차관계는 특징링크(feature link)를 생성하여 시차를 결정한다. 만약, 이 과정에서 시차가 결정되지 않은 특징점들이 있다면, 특징창 내의 결정된 시차 정보를 이용하여 시차 값을 보간한다. 마지막으로, 제안하는 방법의 성능을 검증하기 위해 결과 영상과 정답 영상의 시차를 비교하여 정합 정확성과 수행시간을 비교하였다. 또한, 기존의 특징점 기반 스테레오 정합 방법들과 제안하는 방법의 성능을 비교 및 분석하였다.

• 한국통신학회논문지
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• 제35권8C호
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• pp.680-688
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• 2010

본 논문에서는 영상 분할(image segmentation)을 이용한 다이내믹 프로그래밍(dynamic programming, DP) 기반의 스테레오 정합 (stereo matching)기법을 제안한다. 다이내믹 프로그래밍은 스테레오 정합을 포함하는 여러 가지 컴퓨터 비젼 문제들의 고전적이고 인기가 있는 최적화 방법이다. 그러나 스테레오 정합 문제에 적용될 때 스캔라인들 사이의 수직 상호 관계가 적절하게 고려되지 않기 때문에 기존의 DP의 성능은 만족스럽지 않다. 본 논문에서 제안하는 알고리즘에서는 영상을 분할하여 정확한 경계정보를 획득한 다음 경계 정보에 의거하여 변이의 불연속과 폐색영역을 고려한다. Middlebury 스테레오 영상에 적용한 실험 결과들은 제안된 알고리즘이 이전의 다이내믹 기반 알고리즘보다 더 좋은 성능을 보여주는 것을 입증해준다.

• 전자공학회논문지SC
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• 제37권2호
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• pp.50-59
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• 2000

스테레오 영상(stereo image)이란 같은 물체나 장면을 담고있는 서로 다른 시점의 두 영상이며 스테레오 영상에서 깊이 정보를 얻어내는 것을 스테레오 비전(stereo vision)이라 한다. 스테레오 비전에서 가장 중요한 과정은 두 영상에서 서로 일치하는 점을 찾아내는 스테레오 정합(stereo matching)이다. 그러나, 스테레오 정합은 매우 많은 계산을 필요로 하기 때문에 실시간으로 정합하기 어렵다. 본 논문에서는 실시간으로 스테레오 정합을 처리할 수 있는 스테레오 영상 정합 프로세서(stereo image match procesor：SIMP)를 설계하고 구현하였다. 이를 위해 슬라이딩 메모리(sliding memory)와 최소 선택 트리(minimum selection tree)를 제안하였고 파이프라인 구조(pipeline architecture)와 병렬 처리 기법을 이용하였다. SIMP의 입력은 64 그레이 레벨인 두 개의 64×64 스테레오 영상이고 출력은 최대 7의 값을 가지는 변이(disparity)와 12비트의 주소로 이들을 이용하여 64×64 변이도(disparity map)를 구성할 수 있다. SIMP는 약 240 프레임/초의 속도로 스테레오 영상을 처리할 수 있다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1175-1180
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• 1991

The purpose of this paper is to improve the matching accuracy in identifying corresponding points in the area-based matching for the processing of stereo vision. For the selection of window size, a new method is proposed based on frequency domain analysis. The effectiveness of the proposed method is confirmed through a series of experiments. To overcome disproportionate distortion in stereo image pair, a new matching method using the warped window is also proposed. In the algorithm, the window is warped according to imaging geometry. Experiments on a synthetic image show that the matching accuracy is improved by 14.1% and 4.2% over the rectangular window method and image warping method each.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.182-187
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• 1999

Stereo matching is one of the most crucial parts in DEM generation. Naive stereo matching algorithms often create many holes and blunders in a DEM and therefore a carefully designed strategy must be employed to guide stereo matching algorithms to produce “good” 3D information. In this paper, we describe one such a strategy designed by the use of scene geometry, in particular, the epipolarity for generation of a DEM from linear pushbroom images. The epipolarity for perspective images is a well-known property, i.e., in a stereo image pair, a point in the reference image will map to a line in the search image uniquely defined by sensor models of the image pair. This concept has been utilized in stereo matching by applying epipolar resampling prior to matching. However, the epipolar matching for linear pushbroom images is rather complicated. It was found that the epipolarity can only be described by a Hyperbola- shaped curve and that epipolar resampling cannot be applied to linear pushbroom images. Instead, we have developed an algorithm of incorporating such epipolarity directly in least squares correlation matching. Experiments showed that this approach could improve the quality of a DEM.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.3044-3046
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• 2000

A Stereo matching has been an important tool for reconstructing three dimensional terrain. In this stereo matching process, DEM(Digitai Elevation Map) can be generated by the disparity from reference image to target image. Generally disparity map in matching process can be implemented by wraping from reference image to target image and if the role of reference and target is interchanged, the different DEM can be obtained. To evaluate the generated DEM from matching process, We adapted the Photorealistic synthetic image generator using ray tracing technique. The generator produce two simulated image from previous DEM and Ortho-image which is regard as Ground-truth. In this paper, we are concern about estimating more accurate DEM from these two DEMs. The several fusion methods of two DEMs are proposed to generate accurate DEM and compared with previous method. one of fusion methods is by using Cross-Correlation match score and the true DEM should have a high matching score.

• ETRI Journal
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• 제35권6호
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• pp.1011-1020
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• 2013

In this paper, we present a method for obtaining a high-quality 3D depth. The advantages of active pattern projection and passive stereo matching are combined and a system is established. A diffractive optical element (DOE) is developed to project the active pattern. Cross guidance (CG) and auto guidance (AG) are proposed to perform the passive stereo matching in a stereo image in which a DOE pattern is projected. When obtaining the image, the CG emits a DOE pattern periodically and consecutively receives the original and pattern images. In addition, stereo matching is performed using these images. The AG projects the DOE pattern continuously. It conducts cost aggregation, and the image is restored through the process of removing the pattern from the pattern image. The ground truth is generated to estimate the optimal parameter among various stereo matching algorithms. Using the ground truth, the optimal parameter is estimated and the cost computation and aggregation algorithm are selected. The depth is calculated and bad-pixel errors make up 4.45% of the non-occlusion area.

• Journal of information and communication convergence engineering
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• 제9권1호
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• pp.83-88
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• 2011

Abstract. Image segmentation is always a challenging task in computer vision as well as in pattern recognition. Nowadays, this method has great importance in the field of stereo vision. The disparity information extracting from the binocular image pairs has essential relevance in the fields like Stereoscopic (3D) Imaging Systems, Virtual Reality and 3D Graphics. The term 'disparity' represents the horizontal shift between left camera image and right camera image. Till now, many methods are proposed to visualize or estimate the disparity. In this paper, we present a new technique to visualize the horizontal disparity between two stereo images based on image segmentation method. The process of comparing left camera image with right camera image is popularly known as 'Stereo-Matching'. This method is used in the field of stereo vision for many years and it has large contribution in generating depth and disparity maps. Correlation based stereo-matching are used most of the times to visualize the disparity. Although, for few stereo image pairs it is easy to estimate the horizontal disparity but in case of some other stereo images it becomes quite difficult to distinguish the disparity. Therefore, in order to visualize the horizontal disparity between any stereo image pairs in more robust way, a novel stereo-matching algorithm is proposed which is named as "Quadtree Segmentation of Pixels Disparity Estimation (QSPDE)".

• 반도체디스플레이기술학회지
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• 제15권4호
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• pp.103-106
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• 2016

3D technology is main factor in Augmented Reality. Depth map is essential to make cubic effect using 2d image. There are a lot of ways to construct Depth map. Among them, stereo matching is mainly used. This paper presents how to generate depth map using stereo matching. For stereo matching, existing Dynamic programming method is used. To make accurate stereo matching, High-Boost Filter is applied to preprocessing method. As a result, when depth map is generated, accuracy based on Ground Truth soared.

• Korean Journal of Geomatics
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• 제1권1호
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• pp.43-49
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• 2001

Although many kinds of stereo matching method have been developed in the field of computer vision and photogrammetry, wrong matches are not easy to avoid. This paper presents a new method to reduce wrong matches after matching, and experimental results are reported. The main idea is to analyze the histogram of the image attribute differences between each pair of image patches matched. Typical image attributes of image patch are the mean and the standard deviation of gray value for each image patch, but there could be other kinds of image attributes. Another idea is to check relative position among potential matches. This paper proposes to use Gaussian blunder filter to detect the suspicious pair of candidate match in relative position among neighboring candidate matches. If the suspicious candidate matches in image attribute difference or relative position are suppressed, then many wrong matches are removed, but minimizing the suppression of good matches. The proposed method is easy to implement, and also has potential to be applied as post processing after image matching for many kinds of matching methods such as area based matching, feature matching, relaxation matching, dynamic programming, and multi-channel image matching. Results show that the proposed method produces fewer wrong matches than before.