• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.4
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• pp.285-292
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• 2013

This study proposes a network matching method based on a network division technique. The proposed method generates polygons surrounded by links of the original network dataset, and detects corresponding polygon group pairs using a intersection-based graph clustering. Then corresponding sub-network pairs are obtained from the polygon group pairs. To perform the geometric correction between them, the Iterative Closest Points algorithm is applied to the nodes of each corresponding sub-networks pair. Finally, Hausdorff distance analysis is applied to find link pairs of networks. To assess the feasibility of the algorithm, we apply it to the networks from the KTDB center and commercial CNS company. In the experiments, several Hausdorff distance thresholds from 3m to 18m with 3m intervals are tested and, finally, we can get the F-measure of 0.99 when using the threshold of 15m.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.907-917
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• 2019

Recently, the demand for high-resolution satellite images increases in many fields such as land monitoring and terrain analysis. Therefore, the need for geometric correction is increasing. As an automatic precision geometric correction method, there is a method of automatically extracting the GCP by matching between the GCP Chip and the satellite image. For automatic precision geometric correction, the success rate of matching GCP Chip and satellite image is important. Therefore, it is important to evaluate the matching performance of the manufactured GCP Chip. In order to evaluate the matching performance of GCP Chips, a total of 3,812 GCP Chips in South Korea were used as experimental data. The GCP Chip matching results of KOMPSAT-3A and Google Map showed similar matching results. Therefore, we determined that Google Map satellite imagery could replace high-resolution satellite imagery. Also, presented a method using center point and error radius of Google Map to reduce the time required to verify matching performance. As a result, it is best to set the optimum error radius to 8.5m. Evaluated the matching performance of GCP Chips in South Korea using Google Maps. And verified matching result using presented method. As a result, the GCP Chip s in South Korea had a matching success rate of about 94%. Also, the main matching failure factors were analyzed by matching failure GCP Chips. As a result, Except for GCP Chips that need to be remanufactured, the remaining GCP Chips can be used for the automatic geometric correction of satellite images.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.847-859
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• 2021

Recently, as the number of high-resolution satellite SAR images increases, the demand for precise matching of SAR imagesin change detection and image fusion is consistently increasing. RMSE (Root Mean Square Error) values using GCPs (Ground Control Points) selected by analysts have been widely used for quantitative evaluation of image registration results, while it is difficult to find an approach for automatically measuring the registration accuracy. In this study, a feasibility analysis was conducted on using the FSIM (Feature Similarity) index as a measure to evaluate the registration accuracy. TerraSAR-X (TSX) staring spotlight data collected from various incidence angles and orbit directions were used for the analysis. FSIM was almost independent on the spatial resolution of the SAR image. Using a single SAR image, the FSIM with respect to registration errors was analyzed, then use it to compare with the value estimated from TSX data with different imaging geometry. FSIM index slightly decreased due to the differencesin imaging geometry such as different look angles, different orbit tracks. As the result of analyzing the FSIM value by land cover type, the change in the FSIM index according to the co-registration error was most evident in the urban area. Therefore, the FSIM index calculated in the urban was mostsuitable for determining the accuracy of image registration. It islikely that the FSIM index has sufficient potential to be used as an index for the co-registration accuracy of SAR image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.2A
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• pp.137-145
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• 2002

In the method of 3D modeling, stereo matching method which obtains three dimensional depth information from the two images is taken from the different view points. In general, it is very essential work for the 3D modeling from 2D stereo images to estimate the exact disparity through fading the conjugate pair of pixel from the left and right image. In this paper to solve the problems of the stereo image disparity estimation, we introduce a novel approach method to improve the exactness and efficiency of the disparity. In the first place, we perform a wavelet transformation of the stereo images and set the reference points in the image by the feature-based matching method. This reference points have very high probability over 95 %. In the base of these reference points we can decide the size of the variable block searching windows for estimating dense disparity of area based method and perform the ordering constraint to prevent mismatching. By doing this, we could estimate the disparity in a short time and solve the occlusion caused by applying the fried-sized windows and probable error caused by repeating patterns.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.559-561
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• 2001

본 논문에서는 스테레오 영상으로부터 변위를 추정할 수 있는 다양한 방법들 중 특정 기반 방식과 영역 기반 방식의 각각의 장점들을 살리고 단점들을 보완하기 위한 방법은 제안한다. 영상의 경계선을 이루는 특징점들은 전체 영상의 5% 내외의 소수로 추출되면서도 많은 양의 영상 정보를 가지고 있으므로, 이 점들에 대해 일정한 매칭 과정을 통해 대응점을 구하고, 이 중 90% 이상의 정확성 매칭 확률을 가진 대응점들을 영상으로 기준점으로 설정한다. 그리고 이러한 기준점 이외의 점들에 대해서는 추출된 기준점들의 순서에 맞추어 Ordering Constraint를 적용시키고 기준점에 따라 블록의 크기가 달라지는 영역 기반 방식을 적용하여 조밀한 변위를 추정하였다. 이렇게 함으로써 영역 기반 방식과 특징 기반 방식의 각각의 장점들을 이용하면서도 특정기반 방식의 문제점인 보간법 문제를 해결하였고, 또한 블록의 크기 따라 계산 시간과 정합 오차가 많이 좌우되는 영역 기반 방식의 단점들을 해결하였다. 또한 기준점을 이용하여 Ordering constraint 기반하에 영역 정보를 이용하므로 좀 더 올바른 순서 조건에 맞추어 대응점을 찾을 수 있고 또한 폐쇄 영역 부분도 쉽게 찾을 수 있었다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.4
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• pp.321-330
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• 1999

Automation of observation and positioning of fiducial marks is made possible with the application of image matching technique, developed through the cooperative research effort of computer vision and digital photogrammetry. The major problem in such automation effort is to minimize the computing time and to increase the positional accuracy. Except for scanning and ground control surveying, the interior orientation process was automated in this study, through the development of an algorithm which applies the image matching and image processing techniques. The developed system was applied to close-range photogrammetry and the analysis of the results showed 54% improvement in processing time. For fiducial mark observation during interior orientation, the Laplacian of Gaussian transformation and the Hough transformation were applied to determine the accurate position of the center point, and the correlation matching and the least squares matching method were then applied to improve the accuracy of automated observation of fiducial marks. Image pyramid concept was applied to reduce the computing time of automated positioning of fiducial mark.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.73-76
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• 2008

We present a area-based method for stereo matching using varying weights. A central problem in a area-based stereo matching is different result from selecting a window size. Most of the previous window-based methods iteratively update windows. However, the iterative methods very sensitive the initial disparity estimation and are computationally expensive. To resolve this problem, we proposed a new function to assign weights to pixels using features. To begin with, we extract features in a given stereo images based on edge. We adjust the weights of the pixels in a given window based on correlation of the stereo images. Then, we match pixels in a given window between the reference and target images of a stereo pair. The proposed method is compared to existing matching strategies using both synthetic and real images. The experimental results show the improved accuracy of the proposed method.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.815-822
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• 2003

Fingerprint image enhancement and minutiae matching are two key steps in an automatic fingerprint identification system. In this paper, we propose a fingerprint recognition technique by using minutiae linking information. Recognition process have three steps ; preprocessing, minutiae extraction, matching step based on minutiae pairing. After extracting minutiae of a fingerprint from its thinned image for accuracy, we introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection with low cost in comparison stage of two fingerprints. This algorithm is invariable to translation and rotation of fingerprint. The matching algorithm was tested on 500 images from the semiconductor chip style scanner, experimental result revealed the false acceptance rate is decreased and genuine acceptance rate is increased than existing method.

• Progress in Medical Physics
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• v.14 no.3
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• pp.196-202
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• 2003

In 3-dimensional conformal radiation therapy (3D-CRT) and intensity-modulated radiation therapy (IMRT), many studies on reducing setup error have been conducted in order to focus the irradiation on the tumors while sparing normal tissues as much as possible. As one of these efforts, we developed an image enhancement and registration tool for simulators and portal images that analyze setup errors in a quantitative manner. For setup verification, we used simulator (films and EC-L films (Kodak, USA) as portal images. In addition, digital-captured images during simulation, and digitally-reconstructed radiographs (DRR) can be used as reference images in the software, which is coded using IDL5.4 (Research Systems Inc., USA). To improve the poor contrast of portal images, histogram-equalization, and adaptive histogram equalization, CLAHE (contrast limited adaptive histogram equalization) was implemented in the software. For image registration between simulator and portal images, contours drawn on the simulator image were transferred into the portal image, and then aligned onto the same anatomical structures on the portal image. In conclusion, applying CLAHE considerably improved the contrast of portal images and also enabled the analysis of setup errors in a quantitative manner.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.221-232
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• 2021

This study analyzed co-registration results according to the geometric processing level of reference image, which are Level 1R and Level 1G provided from KOMPSAT-3 and KOMPSAT-3A images. We performed co-registration using each Level 1R and Level 1G image as a reference image, and Level 1R image as a sensed image. For constructing the experimental dataset, seven Level 1R and 1G images of KOMPSAT-3 and KOMPSAT-3A acquired from Daejeon, South Korea, were used. To coarsely align the geometric position of the two images, SURF (Speeded-Up Robust Feature) and PC (Phase Correlation) methods were combined and then repeatedly applied to the overlapping region of the images. Then, we extracted tie-points using the SURF method from coarsely aligned images and performed fine co-registration through affine transformation and piecewise Linear transformation, respectively, constructed with the tie-points. As a result of the experiment, when Level 1G image was used as a reference image, a relatively large number of tie-points were extracted than Level 1R image. Also, in the case where the reference image is Level 1G image, the root mean square error of co-registration was 5 pixels less than the case of Level 1R image on average. We have shown from the experimental results that the co-registration performance can be affected by the geometric processing level related to the initial geometric relationship between the two images. Moreover, we confirmed that the better geometric quality of the reference image achieved the more stable co-registration performance.