• Annual Conference of KIPS
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• 2005.05a
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• pp.1619-1622
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• 2005

본 논문에서는 로봇이 작업을 계획하기 위해 필요한 3차원 작업 공간을 세 가지의 컨텍스트(context)들을 이해함으로써 빠르게 모델링하는 새로운 기법을 소개 하고 있다. 로봇이 사람과 비슷한 속도와 정확도로 작업 공간을 이해하고 모델링하는 것에 초점을 두고 있으며 이를 위해 작업 공간상의 특징적인 세 가지의 컨텍스트(작업공간의 간략화를 위한 전체 공간상의 평면특징, 데이터베이스에 미리 정의된 물체 그리고 로봇의 주어진 작업에 따라 다양한 상세함을 갖는 그 외의 장애물)를 정의하였고, 그것들을 빠르게 이해함으로써 어떻게 3차원 작업 공간을 형성하는지 설명하고 있다. 본 논문에서 3 차원 정보를 갖는 scale invariant feature transformation(SIFT)를 stereo-sis SIFT 로 간주했으며 이를 이용하여 위에서 언급한 컨텍스트들을 이해하였고 다양한 카메라의 위치로부터 얻어지는 여러 개의 장면들을 정합하였다. 또한, 실험을 통해 제안한 방법의 타당성도 검증하였다.

• Journal of IKEEE
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• v.19 no.4
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• pp.460-464
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• 2015

This paper proposes a panoramic image stitching that operates in real time at the embedded environment by applying ROI and PROSAC algorithm. The conventional panoramic image stitching applies SURF or SIFT algorithm which contains complicated operations and a lots of data, at the overall image to detect feature points. Also it applies RANSAC algorithm to remove outliers, so that an additional verification time is required due to its randomness. In this paper, unnecessary data are eliminated by setting ROI based on the characteristics of panorama images, and PROSAC algorithm is applied for removing outliers to reduce verification time. The proposed method was implemented on the ORDROID-XU board with ARM Cortex-A15. The result shows an improvement of about 54% in the processing time compared to the conventional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.213-231
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• 2014

Existing image search systems allow users to search images by keywords, or by example images through content-based image retrieval (CBIR). On the other hand, users might learn more relevant textual information about an image from its text captions or surrounding contexts within documents or Web pages. Without such contexts, it's difficult to extract semantic description directly from the image content. In this paper, we propose an annotation watermarking system for users to embed text descriptions, and retrieve more relevant textual information from similar images. First, tags associated with an image are converted by two-dimensional code and embedded into the image by discrete wavelet transform (DWT). Next, for images without annotations, similar images can be obtained by CBIR techniques and embedded annotations can be extracted. Specifically, we use global features such as color ratios and dominant sub-image colors for preliminary filtering. Then, local features such as Scale-Invariant Feature Transform (SIFT) descriptors are extracted for similarity matching. This design can achieve good effectiveness with reasonable processing time in practical systems. Our experimental results showed good accuracy in retrieving similar images and extracting relevant tags from similar images.

• Journal of Urban Science
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• v.12 no.2
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• pp.43-52
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• 2023

UAV have the disadvantage that are weak from rainfall or winds due to the light platform, so use Scale-Invariant Feature Transform (SIFT) method which extrude keypoints in image matching process. To find the efficient filtering method for the construction of precise Digital Terrain Model (DTM) using UAV images, comparatively analyzed sobel and Differential of Gaussian (DoG) and found sobel is more efficient way to extrude buildings, trees, and so on. And edges are extruded more clearly when applying median additionally which have the merit of preserving edge and eliminating noise. In this study, applied sobel-median filtering which plus median to sobel and constructed the 1st filtered DTM that extrude building and trees and 2nd filtered DTM that extrude cars by threshold of gradient, Analysis of the degree of accuracy improvement showed that standard deviations of 1st filtered DTM and 2nd filtered DTM are 0.32m, 0.287m respectively, and both are acceptable for the tolerance of 0.33m for elevation points of 1/1,000 digital map, and the accuracy was increased about 10% by filtering automobiles. Plus, moving things are changed those position and direction in every image, and these are not target to filter because of the characteristic that is excluded from SIFT method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2271-2283
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• 2015

In this paper, we propose a method which infers an accurate disparity map for radiometrically varying stereo images. For this end, firstly, we transform the input color images to the log-chromaticity color space from which a linear relationship can be established during constructing a joint pdf between input stereo images. Based on this linear property, we present a new stereo matching cost by combining weighted mutual information and the SIFT (Scale Invariant Feature Transform) descriptor with segment-based plane-fitting constraints to robustly find correspondences for stereo image pairs which undergo radiometric variations. Experimental results show that our method outperforms previous methods and produces accurate disparity maps even for stereo images with severe radiometric differences.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.630-638
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• 2016

In this paper, a feature based panorama image generation algorithm using FAST(Features from Accelerated Segment Test) method that is faster than SIFT(Scale Invariant Feature Transform) and SURF(Speeded Up Robust Features) is proposed. Cylindrical projection is performed to generate natural panorama images with numerous images as input. The occurred error can be minimized by applying RANSAC(Random Sample Consensus) for the matching process. When we synthesize numerous images acquired from different camera angles, we use blending techniques to compensate the distortions by the heterogeneity of border line. In that way, we could get more natural synthesized panorama image. The proposed algorithm can generate natural panorama images regardless the order of input images and tilted images. In addition, the image matching can be faster than the conventional method. As a result of the experiments, distortion was corrected and natural panorama image was generated.

• Journal of Internet of Things and Convergence
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• v.2 no.4
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• pp.15-20
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• 2016

This paper describes the construction of knowledge data retrieval management system based on medical image CT. The developed system is aimed to improve the efficiency of the hospital by reading the medical images using the intelligent retrieval technology and diagnosing the patient 's disease name. In this study, the medical image DICOM file of PACS is read, the image is processed, and feature values are extracted and stored in the database. We have implemented a system that retrieves similarity by comparing new CT images required for medical treatment with the feature values of other CTs stored in the database. After converting 100 CT dicom provided for academic research into JPEG files, Code Book Library was constructed using SIFT, CS-LBP and K-Mean Clustering algorithms. Through the database optimization, the similarity of the new CT image to the existing data is searched and the result is confirmed, so that it can be utilized for the diagnosis and diagnosis of the patient.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.5
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• pp.477-486
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• 2020

Drone has been widely used for many applications ranging from amateur and leisure to professionals to get fast and accurate 3-D information of the surface of the interest. Most of commercial softwares developed for this purpose are performing automatic matching based on SIFT (Scale Invariant Feature Transform) or SURF (Speeded-Up Robust Features) using nadir-looking stereo image sets. Since, there are some situations where not only nadir and nadir-looking matching, but also nadir and oblique-looking matching is needed, the existing software for the latter case could not get good results. In this study, a matching experiment was performed to utilize images with differences in geometry. Nadir and oblique-looking images were acquired through drone for a total of 2 times. SIFT, SURF, which are feature point-based, and IMAS (Image Matching by Affine Simulation) matching techniques based on affine transformation were applied. The experiment was classified according to the identity of the geometry, and the presence or absence of a building was considered. Images with the same geometry could be matched through three matching techniques. However, for image sets with different geometry, only the IMAS method was successful with and without building areas. It was found that when performing matching for use of images with different geometry, the affine transformation-based matching technique should be applied.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.222-225
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• 2011

영상 매칭은 컴퓨터 비전에서 중요한 기초 기술 중에 하나이다. 하지만 스케일, 회전, 조명, 시점변화에 강인한 대응점을 찾는 것은 쉬운 작업이 아니다. 이러한 문제점을 보안하기 위해서 스케일 불변 특징 변환(Scale Invariant Feature Transform) 고속의 강인한 특징 추출(Speeded up robust features) 알고리즘등에 제안되었지만, 시점 변화에 있어서 취약한 문제점을 나타냈다. 본 논문에서는 이런 문제점을 해결하기 위해서 시점 변화에 강인한 알고리즘을 제안하였다. 시점 변화에 강인한 영상매칭을 위해서 원본 영상과 질의 영상간 유사도 높은 특징점들의 호모그래피 변환을 이용해서 질의 영상을 원본 영상과 유사하게 보정한 뒤에 매칭을 통해서 시점 변화에 강인한 알고리즘을 구현하였다. 시점이 변화된 여러 영상을 통해서 기존 SIFT,SURF와 성능과 수행 시간을 비교 함으로서, 본 논문에서 제안한 알고리즘의 우수성을 입증 하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5506-5521
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• 2017

Three-dimensional video (3DV), as the new generation of video format standard, can provide the viewers with a vivid screen sense and a realistic stereo impression. Meanwhile the view synthesis has become an important issue for 3DV application. Differently from the conventional methods based on depth, in this paper we propose a new view synthesis algorithm, which can employ the correlation among views and warp in the image domain only. There are mainly two contributions. One is the incorporation of sobel edge points into feature extraction and matching, which can obtain a better stable homography and then a visual comfortable synthesis view compared to SIFT points only. The other is a novel image blending method proposed to obtain a better synthesis image. Experimental results demonstrate that the proposed method can improve the synthesis quality both in subjectivity and objectivity.