• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.6
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• pp.122-129
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• 2016

There have been a lot of researches on object recognition in computer vision. The SURF(Speeded Up Robust Features) algorithm based on feature detection is faster and more accurate than others. However, this algorithm has a shortcoming of making an error due to feature point mismatching when extracting feature points. In order to increase a success rate of object recognition, we have created an object recognition system based on SURF and RANSAC(Random Sample Consensus) algorithm and proposed the pattern recognition filtering. We have also presented experiment results relating to enhanced the success rate of object recognition.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.161-166
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• 2007

Multi-functional Transport Satellite lR(MTSAT-lR)과 같은 정지궤도 기상위성의 지상 전처리 과정에는 영상위치보정(Image navigation and registration)이 포함된다. 영상위치보정은 위성 영상의 기하학적인 왜곡을 보정하는 과정이다. 랜드마크를 이용하는 영상위치보정 과정은 랜드마크 결정과 센서 모델 추정， 리샘플링(Resampling)의 세 가지 단계로 나눌 수 있다. MTSAT-1R의 High Resolution Image Data(HiRID)는 이미 영상위치보정이 수행되었지만, 기하학적인 오차가 남아있는 영상을 포함하기도 한다. 본 연구에서는 이런 기하학적인 오차를 제거하기 위해서 강인추정 기법에 기반한 기하보정을 수행하였다. 이태윤 등 (2005)은 강인추정 기법과 Direct Linear Transformation (DLT)에 기반한 오정합 판별 방법을 제안하였다. 이 판별 방법을 적용하여 추정된 DLT로 MTSAT-1R 영상의 기하보정을 수행한 결과에는 향상된 정확도로 기하보정 된 영상 뿐만 아니라 비교적 큰 오차를 포함하는 영상도 있었다. 이를 해결하기 위해서 본 연구에서는 강인추정 기법과 Affine 변환을 이용한 방법을 적용하였다. 본 연구에서는 기준 해안선에서 추출한 1,407개의 랜드마크와 8개의 MTSAT-1R 영상을 이용하였으며，강인추정 기법에 DLT를 적용한 방법과 Affine 변환을 적용한 방법으로 자동 기하보정을 수행하여 그 결과를 비교하였다. 또한 강인추정 기볍 중 RANSAC과 MSAC의 적용 결과를 비교하여 보았다. 그 결과，DLT로 기하보정 시，본 논문에서 제안된 방법이 강인추정 기법에 DLT를 적용한 방법 보다 더 좋은 성능을 보여주었다.

• Journal of Broadcast Engineering
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• v.13 no.6
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• pp.915-929
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• 2008

In this paper, we propose an algorithm for pixel-based disparity estimation with reliability in the multi-view image. The proposed method estimates an initial disparity map using edge information of an image, and the initial disparity map is used for reducing the search range to estimate the disparity efficiently. Furthermore, disparity-mismatch on object boundaries and textureless-regions get reduced by adaptive block size. We generated intermediate-view images to evaluate the estimated disparity. Test results show that the proposed algorithm obtained $0.1{\sim}1.2dB$ enhanced PSNR(peak signal to noise ratio) compared to conventional block-based and pixel-based disparity estimation methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.1C
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• pp.56-63
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• 2003

In this paper, a wavelet-based stereo matching algorithm to obtain an accurate disparity map in wavelet transformed domain by using a shift ability property, a modified wavelet transform, the similarities for their sub-bands, and a hierarchical structure is proposed. New approaches for stereo matching by lots of feature information are to utilize translation-variant results of the sub-bands in the wavelet transformed domain because they cannot literally expect translation invariance in a system based on convolution and sub-sampling. After the similarity matching for each sub-band, we can easily find optimal matched-points because the sub-bands appearance of the shifted signals is definitely different from that of the original signal with no shift.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5856-5864
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• 2011

In this paper, we propose a moving object detection method in road video sequences acquired from a stationary camera. Our proposed method is based on the background subtraction method using Gaussian pyramids in both the background images and input video frames. It is more effective than pixel based subtraction approaches to reduce false detections which come from the mis-registration between current frames and the background image. And to determine a threshold value automatically in subtracted images, we calculate the threshold value using Otsu's method in each frame and then apply a scalar Kalman filtering to the threshold value. Experimental results show that the proposed method effectively detects moving objects in road video images.

• 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.

• Journal of Broadcast Engineering
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• v.18 no.1
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• pp.31-42
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• 2013

This paper proposes a photogrammetric rectification method based on Bayesian approach as a method that eliminates vertical parallax between stereo images to minimize visual fatigue of 3D contents. The image rectification consists of two phases; geometry estimation and epipolar transformation. For geometry estimation, coplanarity-based relative orientation algorithm was used in this paper. To ensure robustness for mismatch and localization error occurred by automation of tie point extraction, Bayesian approach was applied by introducing several prior constraints. As epipolar transformation perspective transformation was used based on condition of collinearity to minimize distortion of result images and modification for input images. Other algorithms were compared to evaluate performance. For geometry estimation, traditional relative orientation algorithm, 8-points algorithm and stereo calibration algorithm were employed. For epipolar transformation, Hartley algorithm and Bouguet algorithm were employed. The evaluation results showed that the proposed algorithm produced results with high accuracy, robustness about error sources and minimum image modification.

• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1369-1376
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• 2012

In this paper, we propose 2D industrial image registration method for the detection of defects. Proposed method performs preprocessing to smooth the original image with the preservation of the edge for the robust registration against general noise. Then, x-direction gradient magnitude image and corresponding binary image are generated. Density analysis around neighborhood regions per pixel are performed to generate feature image for preventing mis-registration due to moire-like patterns, which frequently happen in industrial images. Finally, 2D image registration based on phase correlation between feature images is performed to calculate translational parameters to align two images rapidly and optimally. Experimental results showed that the registration accuracy of proposed method for the real industrial images was 100% and our method was about twenty times faster than the previous method. Our fast and accurate method could be used for the real industrial applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.610-617
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• 2002

In this paper, a new intermediate view reconstruction technique by using a disparity estimation method based-on the adaptive matching window size is proposed. In the proposed method, once the feature values are extracted from the input stereo image, then the matching window size for the intermediate view reconstruction is adaptively selected in accordance with the magnitude of this feature values. That is, coarse matching is performed in the region having smaller feature values while accurate matching is carried out in the region having larger feature values by comparing with the predetermined threshold value. Accordingly, this new approach is not only able to reduce the mismatching probability of the disparity vector mostly happened in the accurate disparity estimation with a small matching window size, but is also able to reduce the blocking effect occurred in the disparity estimation with a large matching window size. Some experimental results on the 'Parts' and 'Piano' images show that the proposed method improves the PSNR about 2.32∼4.16dB and reduces the execution time to about 39.34∼65.58% than those of the conventional matching methods.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.2 s.32
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• pp.65-69
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• 2005

Efficient 3D generation of cultural features, such as buildings in urban area is becoming increasingly important for a number of GIS applications. For reconstruction or 3D building in urban area aerial images, satellite images, LIDAR data have been used mainly. In case of automatically extracting and reconstructing of building height using single aerial images or single satellite images, there are a lot of problems, such as mismatching that result from a geometric distortion of optical images. Therefore, researches or integrating optical images and existing 2D GIS data(e.g. digital map) has been in progress. In this paper, we focused on extracting of building height by means or interest points and vortical line locus for reducing matching points. Also we used digital plotter in order to validate for the results in this study using aerial images(1/5,000) and existing digital map(1/1,000).