• 한국측량학회지
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• 제38권2호
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• pp.165-172
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• 2020

There is growing interest in Vision-based video image matching owing to the constantly developing technology of unmanned-based systems. The purpose of this paper is the development of a fast and effective matching technique for the UAV oblique video image. We first extracted initial matching points using NCC (Normalized Cross-Correlation) algorithm and improved the computational efficiency of NCC algorithm using integral image. Furthermore, we developed a triangulation-based outlier removal algorithm to extract more robust matching points among the initial matching points. In order to evaluate the performance of the propose method, our method was quantitatively compared with existing image matching approaches. Experimental results demonstrated that the proposed method can process 2.57 frames per second for video image matching and is up to 4 times faster than existing methods. The proposed method therefore has a good potential for the various video-based applications that requires image matching as a pre-processing.

• 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.

• 한국측량학회지
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• 제29권5호
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• pp.449-457
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• 2011

As automated image processing techniques have been required in multi-temporal/multi-sensor geospatial image applications, use of automated but highly invariant image matching technique has been a critical ingredient. Note that there is high possibility of geometric and spectral differences between multi-temporal/multi-sensor geospatial images due to differences in sensor, acquisition geometry, season, and weather, etc. Among many image matching techniques, the SIFT (Scale Invariant Feature Transform) is a popular method since it has been recognized to be very robust to diverse imaging conditions. Therefore, the SIFT has high potential for the geospatial image processing. This paper presents a performance test results of the SIFT on geospatial imagery by simulating various image differences such as shear, scale, rotation, intensity, noise, and spectral differences. Since a geospatial image application often requires a number of good matching points over the images, the number of matching points was analyzed with its matching positional accuracy. The test results show that the SIFT is highly invariant but could not overcome significant image differences. In addition, it guarantees no outlier-free matching such that it is highly recommended to use outlier removal techniques such as RANSAC (RANdom SAmple Consensus).

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.589-592
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• 1999

Matching is a key problem in computer vision, image analysis and pattern recognition. In this paper a multiscale image matching algorithm by wavelet local extrema is proposed. This algorithm is based on the multiscale wavelet transform of the curvature which can utilize both the information of local extrema positions and magnitudes of transform results. This method has advantages in computational cost to a single scale image matching. It is also rotation-, translation-, and scale-independent image matching method. This matching can be used for the recognition of occluded objects.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1467-1469
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• 2003

Image matching is fundamental process to identify conjugate points on the stereo images. However, standard methods or general solutions for matching problem have not been found yet, in spite of long history. Quality of the matching basically depends on uniqueness of the matching entity and robustness of the algorithm. In this study, conjugate points were extracted by implementing interest operator, then area based matching method was applied to the topographical characteristics of the gray value as the matching entities. The matching entities were utilized based on the concept of the intrinsic image.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 춘계학술발표회논문집
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• pp.171-176
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• 2004

Image matching is fundamental process in photogrammetry and computer vision to identify and to measure corresponding features on the multiple images. Uniqueness of the matching entities and robustness of the algorithm are the key issues that have influence on quality of the matching result. The optimal solution could be obtained by utilizing appropriate matching entities in the first place. In this study, candidate matching points were extracted by interest operator, and an area-based matching method was applied with characteristics of the gray value distribution as the matching entities. The characteristic information is based on the concept of "intrinsic image" (or parameter image). The information was utilized as additional and/or complementary matching entities. Matching on interest points with the characteristic information resulted in high quality of matching because matching windows were created with surrounding pixels of the interest points that contain distinct and unique features. The experiment shows that matching quality and reliability increase by exploiting interest operator, and the characteristic information has potential to be matching entity.

• 한국정보과학회논문지:데이타베이스
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• 제36권4호
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• pp.327-340
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• 2009

본 논문에서는 윤곽선 이미지 매칭에서 노이즈 제거 정도를 제어하기 위해 시계열 매칭의 이동평균 변환을 이용한다. 이동평균 변환을 윤곽선 이미지 매칭에 적용하게 된 동기는 이동평균 변환이 시계열의 노이즈를 감소시키므로, 이를 사용하면 윤곽선 이미지 매칭에서도 노이즈 제어 효과를 얻을 수 있을 것이라는 직관에 기반한다. 본 논문에서는 우선 윤곽선 이미지 매칭에 이동평균 변환을 적용한 $\kappa$-계수 이미지 매칭($\kappa$-order image matching)을 제안한다. 제안한 $\kappa$-계수 이미지 매칭은 윤곽선 이미지가 변환된 시계열에 $\kappa$-이동평균 변환을 적용하여 시계열(이미지) 간의 유사성을 판단한다. 다음으로, 대용량 이미지 데이터베이스를 대상으로 $\kappa$-계수 이미지 매칭을 수행하기 위한 인덱스 기반 매칭 방법을 제안하고, 그 정확성을 정형적으로 증명한다. 또한, 계수 $\kappa$와 매칭 결과와의 관계를 정형적으로 분석하고, 이에 기반하여 계수 $\kappa$를 변화시키면서 노이즈 제거 정도를 제어하는 방안을 제시한다. 실험 결과, $\kappa$-계수 이미지 매칭이 노이즈 제거 효과를 가짐을 확인하였으며, 제안한 인덱스 기반 매칭 방법은 순차 스캔에 비해 수 배 에서 수십 배 빠른 성능을 보이는 것으로 나타났다.

• 한국멀티미디어학회논문지
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• 제20권10호
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• pp.1619-1627
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• 2017

Image hashing has been successfully applied for the problems associated with the protection of intellectual property, management of large database and indexation of content. For a reliable hashing system, improving hash matching accuracy is crucial. In order to improve the hash matching performance, we propose an asymmetric hash matching method using the psychovisual threshold, which is the maximum amount of distortion that still allows the human visual system to identity an image. A performance evaluation over sets of image distortions shows that the proposed asymmetric matching method effectively improves the hash matching performance as compared with the conventional Hamming distance.

• 한국측량학회지
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• 제29권1호
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• pp.101-109
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• 2011

본 논문에서는 다중 항공영상을 이용한 영상정합기법과, 그 성능을 향상시키기 위한 시도들에 대해 기술한다. 일반적으로 영상간의 정합은 하나의 기준영상을 기준으로 다른 영상과의 밝기값 상관계수를 이용한 유사도 분석으로 진행된다. 제안된 다중 영상 정합기법 알고리즘은 처리할 지역을 일정크기의 구역으로 나누고 각 구역에서 가장 정사영상에 가까운 영상을 기준으로 하여 Object space상에서 처리할 수 있는 방식이다. 이 방식을 통해 영상의 위치에 상관없이 균등한 품질의 DEM이 생성 가능함을 확인할 수 있었다. 또한 차폐탐지 및 생성된 차폐지도를 통한 성능 향상 실험을 하였으며 그 결과 더욱 정확한 3차원 정보의 표현이 가능함을 확인할 수 있었다.

• 대한원격탐사학회지
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• 제26권3호
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• pp.325-333
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• 2010

Image registration involves overlapping images of an identical region and assigning the data into one coordinate system. Image registration has proved important in remote sensing, enabling registered satellite imagery to be used in various applications such as image fusion, change detection and the generation of digital maps. The image descriptor, which extracts matching points from each image, is necessary for automatic registration of remotely sensed data. Using contrast enhancement algorithms such as histogram equalization and image stretching, the normalized data are applied to the image descriptor. Drawing on the different spectral characteristics of high resolution satellite imagery based on sensor type and acquisition date, the applied normalization method can be used to change the results of matching interest point descriptors. In this paper, the matching points by scale invariant feature transformation (SIFT) are extracted using various contrast enhancement algorithms and injection of Gaussian noise. The results of the extracted matching points are compared with the number of correct matching points and matching rates for each point.