• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2002.04a
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• pp.187-194
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• 2002

본 논문에서는 SPOT 입체영상을 이용하여 광범위한 지역의 DEM을 제작할 경우 DEM 모자이크 과정에서 발생할 수 있는 접합선(seam-line)을 최소화할 수 있는 방법을 연구하였다. 지상의 60km$\times$60km 영역을 촬영할 수 있는 SPOT 위성의 입체 영상으로부터 구성한 단일 모델은 일반적으로 관심 있는 지역의 DEM을 제작하기에 충분히 넓은 지역을 포함할 수 있다. 그러나 광범위한 지역의 DEM 제작을 위해서는, 각각의 입체영상을 통해 제작된 DEM들을 접합해야 하며, 이 때 발생되는 접합선을 효과적으로 제거하는 작업이 필요하다. 이를 위해 SPOT 위성영상의 블록 조정 방법을 이용하여 종횡접합모델을 구성하고 중복되는 인접한 SPOT DEM간의 표고값을 일치시키므로써 DEM 접합선의 발생을 최소화하여 모자이크시 작업량을 줄이고자 한다. 본 논문에서는 기존의 지상기준점과 추가로 관측한 영상접합점을 이용하여 종횡접합 블록을 구성하고 광속조정 방법을 적용하여 블록에 포함된 위성영상의 외부표정요소를 계산하였다. 블록모델을 이용하여 DEM을 제작할 경우 접합선 탐색 및 blending 작업 없이 단순중첩 방법으로도 DEM 모자이크 작업을 빠르게 수행할 수 있음을 확인하였다.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.211-215
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• 2004

본 연구에서는 2개 이상의 지리 부호화된 영상병합 시 중복 영역의 연결 부분에서 발생하는 방사적 차이를 최소화하여 모자이크 접합선이 최소화하는 알고리즘을 구현하였다. 연구내용을 세부적으로 보면 초기 접합선 및 최적 접합선 탐색을 하는 접합선 추출 알고리즘 구현, 대상 영상의 전체적인 방사 값의 분포 특성을 정규화하는 전역 방사 보정을 위한 알고리즘 구현, 접합선을 자동 탐색하여 탐색된 접합선을 중심으로 단순 중복, 평균화, 블랜딩에 의한 모자이킹 알고리즘 구현이 본 연구의 핵심 내용이다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.483-497
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• 2018

Image mosaicking, which combines several images into one image, is effective for analyzing images and important in various fields of spatial information such as a continuous image map. The crucial processes of the image mosaicking are optimal seamline determination and color correction of mosaicked images. In this study, the overlap regions were determined by SURF (Speeded Up Robust Features) for image matching. Based on the characteristics of the edges extracted by Canny filter, seamline candidates were selected from classified edges with their characteristics, and the edges were connected by using Dijkstra algorithm. In particular, anisotropic filter and image pyramid were applied to extract reliable seamlines. In addition, it was possible to determine seamlines effectively and efficiently by utilizing building and road layers from digital maps. Finally, histogram matching and seamline feathering were performed to improve visual quality of the mosaicked images.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.5
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• pp.30-42
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• 2022

Due to the increase in construction of tunnels, the burdens of maintenance works for tunnel structures have been increasing in Korea. In addition, the increase of traffic volume and aging of materials also threatens the safety of tunnel facilities, therefore, maintenance costs are expected to increase significantly in the future. Accordingly, automated condition assessment technologies like image-based tunnel scanning system for inspection and diagnosis of tunnel facilities have been proposed. For image-based tunnel scanning system, it is key to create a planar image through stitching of multiple images captured by tunnel scanning system. In this study, performance of feature-based stitching algorithms suitable for stitching tunnel scanning images was evaluated. In order to find a suitable algorithm SIFT, ORB, and BRISK are compared. The performance of the proposed algorithm was determined by the number of feature extraction, calculation speed, accuracy of feature matching, and image stitching result. As for stitching performance, SIFT algorithm was the best in all parts of tunnel image. ORB and BRISK also showed satisfactory performance and short calculation time. SIFT can be used to generate precise planar images. ORB and BRISK also showed satisfactory stitching results, confirming the possibility of being used when real-time stitching is required.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.111-118
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• 2014

This paper presents an efficient Markov feature extraction method for detecting splicing forged images. The Markov states used in our method are composed of the difference between DCT coefficients in the adjacent blocks. Various first-order Markov state transition probabilities are extracted as features for splicing detection. In addition, we propose a feature reduction algorithm by analysing the distribution of the Markov probability. After training the extracted feature vectors using the SVM classifier, we determine whether the presence of the image splicing forgery. Experimental results verify that the proposed method shows good detection performance with a smaller number of features compared to existing methods.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.395-408
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• 2015

High-resolution satellite image mosaics are becoming increasingly important in the field of remote sensing image analysis as an essential image processing to create a large image constructed from several smaller images. In this paper, we present an automatic seamline extraction technique and the procedure to generate a mosaic image by this technique. For more effective seamline extraction in the overlap region of adjacent images, an NDVI-based seamline extraction technique is developed, which takes advantage of the computational time and memory. The Normalized Difference Vegetation Index(NDVI) is an index of plant "greeness" or photosynthetic activity that is employed to extract the initial seamline. The NDVI can divide into manmade region and natural region. The cost image is obtained by the canny edge detector and the buffering technique is used to extract the ranging cost image. The seamline is extracted by applying the Dijkstra algorithm to a cost image generated through the labeling process of the extracted edge information. Histogram matching is also conducted to alleviate radiometric distortion between adjacent images acquired at different time. In the experimental results using the KOMPSAT-2/3 satellite imagery, it is confirmed that the proposed method greatly reduces the visual discontinuity caused by geometric difference of adjacent images and the computation time.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.152-159
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• 2014

In this paper, we introduce a run-length for wavelet coefficients and present a image splicing detection method using the statistical moments for the wavelet run-length. Various pre-processings for the suspicious image are performed to emphasize the discontinuous edges caused by the image splicing. The proposed scheme has the merit that can exploit the various statistical characteristics of the wavelet transform. We extracted up to 72 features, and performed training and testing using SVM(support vector machine). Experimental results showed that the proposed method generates similar detection results compared to the existing methods. In addition, we showed the wavelet domain run-length is useful to detect the spliced image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.833-839
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• 2016

In this paper, we propose a selective feature extraction algorithm between Markov transition probability and co-occurrence probability for an effective image splicing detection. The Features used in our method are composed of the difference values between DCT coefficients in the adjacent blocks and the value of Kullback-Leibler divergence(KLD) is calculated to evaluate the differences between the distribution of original image features and spliced image features. KLD value is an efficient measure for selecting Markov feature or Co-occurrence feature because KLD shows non-similarity of the two distributions. After training the extracted feature vectors using the SVM classifier, we determine whether the presence of the image splicing forgery. To verify our algorithm we used grid search and 6-folds cross-validation. Based on the experimental results it shows that the proposed method has good detection performance with a limited number of features compared to conventional methods.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.2 s.29
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• pp.61-66
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• 2004

By the advent of the high-resolution Satellite imagery, there are increasing needs in image mosaicking technology which can be applied to various application fields such as GIS(Geographic Information system). To mosaic images, various methods such as image matching and histogram modification are needed. In this study, automated image mosaicking is performed using image matching method based on the multi-resolution wavelet analysis(MWA). Specifically, both area based and feature based matching method are embedded in the multi-resolution wavelet analysis to construct seam line.; seam points are extracted then polygon clipping method are applied to define overlapped area of two adjoining images. Before mosaicking, radiometric correction is proceeded by using histogram matching method. As a result, mosaicking area is automatically extracted by using polygon clipping method. Also, seamless image is acquired using multi-resolution wavelet analysis.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.418-420
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• 2012

스테레오 매칭의 지역적 방법은 구현의 용이성과 낮은 계산복잡도로 인하여 많은 연구가 진행되고 있다. 하지만 대부분의 지역적 방법들은 영상이 외부환경에 변형되었을 때의 경우를 고려하지 않고 있기 때문에, 외부환경에 의해 많이 변형된 영상에 대해서는 제대로 된 변이 정보를 추출해내지 못한다. 본 논문에서는 양쪽 영상에서 곡선접합을 이용하여 서로 대응되는 영역을 찾는 스테레오 매칭 기법을 제안한다. 제안하는 기법은 조명과 같은 외부요소에 강인한 특징을 가진다. 이 기법은 전 처리나 후처리 과정에서 부가적인 작업의 수행 없이 기법 자체만으로 외부요소에 대한 보상을 실행한다는 면에서 장점을 가진다. 비록 다양한 영상에서 변이를 추출하는 실험 결과, 거시적인 특성을 반영하는 곡선접합만으로도 조명에 의해 변형된 영상에 대해서 변이결과를 추출해내었다. 차후 미시적인 방법과의 결합을 통해, 변이정보의 추출의 정확도를 올릴 수 있을 것 이라고 기대된다.