• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.441-452
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• 2017

Drones are increasingly being used to investigate disaster damage because they can quickly capture images in the air. It is necessary to extract the damaged area by registering the drones and the existing ortho-images in order to investigate the disaster damage. In this process, we might be faced the problem of registering two images with different time and spatial resolution. In order to solve this problem, we propose a new methodology that performs initial image transformation using line pairs extracted from images and association matrix, and final registration of images using linear features to refine the initial transformed result. The applicability of the newly proposed methodology in this study was evaluated through experiments using artifacts and the natural terrain areas. Experimental results showed that the root mean square error of artifacts and the natural terrain was 1.29 pixels and 4.12 pixels, respectively, and relatively high accuracy was obtained in the region with artifacts extracted a lot of linear information.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.2
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• pp.49-56
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• 2008

Image registration is one of the critical techniques of image mosaic which has many applications such as generating panoramas, video monitoring, image rendering and reconstruction, etc. The fundamental tasks of image registration are point features extraction and tracking which take much computation time. KLT(Kanade-Lucas-Tomasi) feature tracker has proposed for extracting and tracking features through image sequences. The aim of this study is to demonstrate the usage of effective and robust KLT feature detector and tracker for an image registration using the sequence image frames captured by UAV video camera. In result, by using iterative implementation of the KLT tracker, the features extracted from the first frame of image sequences could be successfully tracked through all frames. The process of feature tracking in the various frames with rotation, translation and small scaling could be improved by a careful choice of the process condition and KLT pyramid implementation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.93-100
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• 2004

This paper presents a method to integrate the multiple impressions of a finger for improving fingerprint verification performance. Small-sized sensor has advantage that it can be used in many application fields. However, sufficiently large impression of fingerprint is not available due to the small sensing area, and this degrades the verification performance of the system. The proposed method overcomes this problem by combining the information of fingerprints for enrollment. To combine the fingerprints, the alignment process is important first of all. In the proposed algorithm multiple impressions of a finger are coarsely aligned using the corresponding minutiae pairs and then are finely aligned using the Distance Map. We construct an integrated template for enrollment in aligned coordinate system Since this integrated template represents the enlarged finger region, the problem that is occurred by using small sensor can be overcome. Experimental results show that the use of the integrated template of multiple impressions improves the performance of the fingerprint verification system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.76-77
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• 2016

본 논문에서는 영상 인식 기술을 적용하여 보안성능을 향상시킨 잠금장치 구현에 대해 설명한다. 사전에 등록된 이미지를 사용자가 기억하고 있다가 등록된 이미지를 포함하고 있는 전체 그림에서 등록된 이미지 부분만을 사용자가 카메라로 캡처하였을 때 비밀번호 입력을 위한 키패드를 스마트기기에 활성화시키는 방법을 적용한다. 이러한 장치는 영상인식 기술, 안드로이드 앱, 아두이노 플랫폼 등을 이용하여 구현하게 된다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.13-21
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• 2021

High-resolution satellites such as Kompsat-3 and CAS-500 include optical cameras of MS (Multispectral) and PAN (Panchromatic) CCD (Charge Coupled Device) sensors installed with certain offsets. The offsets between the CCD sensors produce geometric discrepancy between MS and PAN images because a ground target is imaged at slightly different times for MS and PAN sensors. For precise pan-sharpening process, we propose a co-registration process consisting the physical sensor modeling and image matching. The physical sensor model enables the initial co-registration and the image matching is carried out for further refinement. An experiment with Kompsat-3 images produced RMSE (Root Mean Square Error) 0.2pixels level of geometric discrepancy between MS and PAN images.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.574-576
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• 2002

2D 영상을 가지고 인식 작업을 수행하는데 있어서 입력 영상의 질은 매우 중요한 요소이다. 특히 얼굴 인식과 같은 실시간 입력 데이터와 미리 등록되어진 데이터와 비교하는 경우는 입력 영상과 등록 영상의 상태 차이가 크면 좋은 알고리즘이라 할지라도 높은 성능을 내기는 힘들다. 즉, 테스트를 위한 입력 영상을 등록 영상의 수준과 유사하게 만들어 전체적인 성능을 높일 수 있는 적응형 방법이 필요하다. 본 논문에서는 유전 알고리즘을 이용하여, 하나의 샘플 이미지에서 환경 의존적인 요소를 제거 하기 위한 최적의 필터 조합과 특징 추출 마스크를 생성하였으며, 그것을 사용하여 인식 테스트를 수행하였다. 가상의 편향조명 노이즈를 첨가한 실험에서 진화 전의 약 25% 인식율은 진화 후 약 92% 까지 향상되었으며, 임의의 임펄스 노이즈에 관한 실험에서도 진화 전의 약 47%의 인식율에서 진화 후 약 84%의 높은 인식율 향상 결과를 보여주었다.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.945-957
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• 2019

In this study, we propose a coarse to fine image registration method for eliminating geometric error between images over agricultural areas acquired using Unmanned Aerial Vehicle (UAV). First, images of agricultural area were acquired using UAV, and then orthophotos were generated. In order to reduce the probability of extracting outliers that cause errors during image registration, the region of interest is selected by using the metadata of the generated orthophotos to minimize the search area. The coarse image registration was performed based on the extracted tie-points using the Speeded-Up Robust Features (SURF) method to eliminate geometric error between orthophotos. Subsequently, the fine image registration was performed using tie-points extracted through the Mutual Information (MI) method, which can extract the tie-points effectively even if there is no outstanding spatial properties or structure in the image. To verify the effectiveness and superiority of the proposed method, a comparison analysis using 8 orthophotos was performed with the results of image registration using the SURF method and the MI method individually. As a result, we confirmed that the proposed method can effectively eliminated the geometric errors between the orthophotos.

• 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.

• Journal of the Korean Society of Radiology
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• v.11 no.4
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• pp.235-240
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• 2017

The purpose of this study is to confirm the safety of the clinical application of image co - registration in steteotactic radiosurgery by evaluating the 3D positioning of magnetic resonance imaging using image co-registration. We performed a retrospective study using three-dimensional coordinate measurement of 32 patients who underwent stereotactic radiosurgery and performed magnetic resonance imaging follow-up using image co-registration. The 3 dimensional coordinate errors were $1.0443{\pm}0.5724mm$ (0.10 ~ 1.89) in anterior commissure and $1.0348{\pm}0.5473mm$ (0.36 ~ 2.24) in posterior commissure. The mean error of MR1 (3.0 T) was lower than that of MR2 (1.5 T). It is necessary to minimize the error of magnetic resonance imaging in the treatment planning using the image co - registration technique and to confirm it.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.9-15
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• 2011

Since PAN(panchromatic) and MS(multispectral) imagery of pushbroom scanner have the offset between PAN and MS CCD(charge coupled device) in the focal plane, PAN and MS images are acquired at different time and angle. Since clouds are fast moving objects, they should lead mis-registration problem with wrong matching points on clouds. The registration of cloudy imagery to recognize and remove the contamination of clouds can be categorized into three classes: (1) cloud is considered as nose and removed (2) employing multi-spectral imagery (3) using multi-temporal imagery. In this paper, method (1) and (3) are implemented and analysed with cloudy pushbroom scanner images.