• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.250-261
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• 1998

The purpose of this paper is to extract fast DEM (Digital Elevation Model) using satellite images. DEM extraction consists of three parts. First part is the modeling of satellite position and attitude, second part is the matching of two images to find corresponding points of them and third part is to calculate the elevation of each point by using the results of the first and second part. The position and attitude modeling of satellite is processed by using GCPs. A area based matching method is used to find corresponding points between the stereo satellite images. The elevation of each point is calculated using the exterior orientation parameters obtained from modeling and conjugate points from matching. In the DEM generation system, matching procedure holds most of a processing time, therefore to reduce the time for matching, a new fast matching algorithm using gradient correlation and fast similarity measure calculation method is proposed. In this paper, the SPOT satellite images, level 1A 6000$\times$6000 panchromatic images are used to extract DEM. The experiment result shows the possibility of fast DEM extraction with the satellite images.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.286-289
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• 2009

This paper presents an effective approach to minimize recursive computations for balancing stereo pairs by using disparity vector errors and its directional histogram. A stereo balancing function is computed from the correspondent pixels between two images, and a simple approach is to find the matching blocks of two images. However, this procedure requires recursive operation, and its computation cost is very high. Therefore, in this paper, we propose an efficient balance method using structural similarity index and a partial re-searching scheme to reduce the computation cost considerably. For this purpose, we determine if re-searching for each block is necessary or not by using the errors and the directional histogram of disparity vectors. Experiment results show that the performance of the proposed approach can save the computations significantly with ignorable image quality degradation compared with full re-search approach.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.145-150
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• 2008

This thesis explores the problem of reconstructing a three-dimensional(3D) scene given a set of images or image sequences of the scene. It describes efficient methods for the 3D reconstruction of static and dynamic scenes from stereo images, stereo image sequences, and images captured from multiple viewpoints. Novel methods for image-based and volumetric modelling approaches to 3D reconstruction are presented, with an emphasis on the development of efficient algorithm which produce high quality and accurate reconstructions. For image-based 3D reconstruction a novel energy minimisation scheme, Iterated Dynamic Programming, is presented for the efficient computation of strong local minima of discontinuity preserving energyy functions. Coupled with a novel morphological decomposition method and subregioning schemes for the efficient computation of a narrowband matching cost volume. the minimisation framework is applied to solve problems in stereo matching, stereo-temporal reconstruction, motion estimation, 2D image registration and 3D image registration. This thesis establishes Iterated Dynamic Programming as an efficient and effective energy minimisation scheme suitable for computer vision problems which involve finding correspondences across images. For 3D reconstruction from multiple view images with arbitrary camera placement, a novel volumetric modelling technique, Embedded Voxel Colouring, is presented that efficiently embeds all reconstructions of a 3D scene into a single output in a single scan of the volumetric space under exact visibility. An adaptive thresholding framework is also introduced for the computation of the optimal set of thresholds to obtain high quality 3D reconstructions. This thesis establishes the Embedded Voxel Colouring framework as a fast, efficient and effective method for 3D reconstruction from multiple view images.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.145-148
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• 2001

This paper presents a phase-based stereo matching algorithm in order to efficiently extract 3-dimensional objects from two 2D images. Conventional phase-based methods, especially using windowed Fourier phases, inherit good properties in the cage of hierarchical approaches, because they basically use a multi-resolution phase map. On the contrary, their computational cost is too heavy. Therefore, a fast hierarchical approach, using multi-resolution phase-based strategy and reducing redundancies of phase calculations based on FFT concept is proposed in this paper. In addition, a structural matching algorithm on the phase domain is presented to improve the matching quality. In experimental results. it is shown that the computation loads are considerably reduced about 8 times and stable outputs are obtained from various images.

• Journal of Electrical Engineering and information Science
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• v.2 no.5
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• pp.79-88
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• 1997

This paper introduces a new energy function, as maximum a posteriori(MAP) estimate of binocular disparity, that can deal with both random dot stereo-gram(RDS) and natural scenes. The energy function uses phase-magnitude as features to detect only the shift for a pair of corrupted conjugate images. Also we adopted Fleet singularity that effectively detects unstable areas of image plant and thus eliminates in advance error-prone stereo mathcing. The multi-scale concept is applied to the multi laser architecture that can search the solutions systematically from coarse to fine details and thereby avoids drastically the local minima. Using mean field approximation, we obtained a compact representation that is suitable for fast computation. In this manner, the energy function satisfies major natural constraints and requirements for implementing parallel relaxation. As an experiment, the proposed algorithm is applied to RDS and natural stereo images. As a result we will see that it reveals good performance in terms of recognition errors, parallel implementation, and noise characteristics.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.414-417
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• 1993

The methods for stereo matching are divided into two techniques: area-based matching and feature-based matching. To find corresponding points by area-based method, it takes a lot of time because there are many points to be matched. Feature-based matching algorithm is often used because with this method it matches only some feature points so that the processing time is fast even though it requires interpolation after matching. In this paper, we propose the smart technique by which we makes features simpler than conventional methods to match an image pair by feature-based matching algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.1
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• pp.136-143
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• 2009

Typically, local methods for stereo matching are fast but have relatively low degree of accuracy while global ones, though costly, can achieve a higher degree of accuracy in retrieving disparity information. Recently, some local methods like the ones based on segmentation or adaptive weights are suggested which achieve more accuracy than global ones. These newly suggested local methods that can estimate more accurate disparity information cannot be easily used since they require more computational costs which increase in proportion to the window size they use. In this paper, we propose the method by using distance weights and pixel difference weights similar to those of the bilateral filter. Specifically, we present constant time O(1) algorithm for the case the distance weights are equal. The suggested method requires constant time for computation regardless of the used window size. Furthermore, experiments show that the matching performance of our method is as good as the ones of other recent methods.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.735-739
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• 2005

This paper presents a new system to estimate the head pose of human in interactive indoor environment that has dynamic illumination change and large working space. The main idea of this system is to suggest a new morphological feature for estimating head angle from stereo disparity map. When a disparity map is obtained from stereo camera, the matching confidence value can be derived by measurements of correlation of the stereo images. Applying a threshold to the confidence value, we also obtain the specific morphology of the disparity map. Therefore, we can obtain the morphological shape of disparity map. Through the analysis of this morphological property, the head pose can be estimated. It is simple and fast algorithm in comparison with other algorithm which apply facial template, 2D, 3D models and optical flow method. Our system can automatically segment and estimate head pose in a wide range of head motion without manual initialization like other optical flow system. As the result of experiments, we obtained the reliable head orientation data under the real-time performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3422-3427
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• 2010

In this paper, we presents a sensor calibration technique using stereo X-ray images to provide efficient inspection of fast moving cargo objects. Stereo X-ray scanned images are acquired from a specially designed equipment which consists of a X-ray source, dual-linear array detector, and a conveyor system. Dual detector is installed so that rectified stereo X-ray images of objects are acquired. Using the stereo X-ray images, we carry out a sensor calibration to find the correspondences between the images and reconstruct 3-D shapes of real objects. Using the Image acquired from the stereo detectors with varying distances, we calculated the GCP(ground control point)of the image. And we figure out the error by comparing calculated GCP and GCP of the real object. The experimental results show the proposed technique can enhance the accuracy of stereo matching and give more efficient visualization for cargo inspection image.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.1-8
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• 2008

The belief propagation method that has been studied recently yields good performance in disparity extraction. The method in which a target function is modeled as an energy function based on Markov random field(MRF), solves the stereo matching problem by finding the disparity to minimize the energy function. MRF models provide robust and unified framework for vision problem such as stereo and image restoration. the belief propagation method produces quite correct results, but it has difficulty in real time implementation because of higher computational complexity than other stereo methods. To relieve this problem, in this paper, we propose a fast algorithm of the belief propagation method. Energy function consists of a data term and a smoothness tern. The data term usually corresponds to the difference in brightness between correspondences, and smoothness term indicates the continuity of adjacent pixels. Smoothness information is created from messages, which are assigned using four different message arrays for the pixel positions adjacent in four directions. The processing time for four message arrays dominates 80 percent of the whole program execution time. In the proposed method, we propose an algorithm that dramatically reduces the processing time require in message calculation, since the message.; are not produced in four arrays but in a single array. Tn the last step of disparity extraction process, the messages are called in the single integrated array and this algorithm requires 1/4 computational complexity of the conventional method. Our method is evaluated by comparing the disparity error rates of our method and the conventional method. Experimental results show that the proposed method remarkably reduces the execution time while it rarely increases disparity error.