• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1508-1512
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• 2005

A real time tracking and matching of the screen cursor corresponding to the iris moving by measuring distance between vertical movement and horizontal movement of iris is presented in this paper. The screen cursor is tracked and matched with the distance md direction moving the center-positioned coordinate of iris. The experimental result shows that the moving of iris and screen cursor are accord with distance and size of screen and the optimal tolerance is reduced the tracking error.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1500-1505
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• 1999

In this paper, we presented the stereo algorithm for 3-D object recognition. In order to solve the problem for matching time in existed methods, we proposed the method which used the moving direction vector. On the other hand, after we extracted the moving vectors by moving direction of objects, rotated object was matched on axis of it. Using the Hough transform, we obtained the 2-D synthesed image as reference images corresponding to the rate of moving, and then compared with the unknown input images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.973-976
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• 2007

본 논문에서는 영상 시퀀스 내의 흔들림을 제거하는 고속 알고리즘을 제안한다. 프레임 지터 제거에 관한 연구는 영상 취득과정에서 발생하는 손떨림에 의한 영향을 제거하거나 오래된 영화필름에서 녹화장치의 기구적인 문제로 인해 발생한 흔들림을 제거하기 위해 많이 연구되었다. 제안하는 알고리즘은 영상 프레임을 배경과 전경 영역으로 나누고 움직임 벡터를 이용하여 천역 움직임을 구한다. 전역 움직임을 구하는 과정에서 잘못된 움직임 예측이 발생할 가능성이 높은 블록을 사전에 제거하여 속도를 개선하였으며 알고리즘을 실제 영상에 적용하여 영상 프레임 정합됨을 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.848-856
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• 2004

In this paper, a fast stereo matching algorithm based on pixel-wise matching strategy, which can get a stable and accurate disparity map, is proposed. Since a stereo image pair has small differences each other and the differences between left and right images are just caused by horizontal shifts with some order, the matching using a large window will not be needed within a given search range. However, disparity results of conventional pixel-based matching methods are somewhat unstable and wrinkled, the principal direction of disparities is checked by the accumulated cost along a path on array with the dynamic programming method. Experimental results showed that the proposed method could remove almost all disparity noise and set a good quality disparity map in very short time.

• Journal of Broadcast Engineering
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• v.18 no.5
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• pp.730-737
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• 2013

In this paper, Constrained One-Bit Transform (C1BT) based motion estimation using extension of matching error criterion is proposed. C1BT based motion estimation algorithm exploiting Number of Non-Matching Points (NNMP) instead of Sum of Absolute Differences (SAD) that used in the Full Search Algorithm (FSA) facilitates hardware implementation and significantly reduces computational complexity. However, the accuracy of motion estimation is decreased. To improve inaccurate motion estimation, this algorithm based motion estimation extending matching error criterion of C1BT is proposed in this paper. Experimental results show that proposed algorithm has better performance compared with the conventional algorithm in terms of Peak-Signal-to-Noise-Ratio (PSNR).

• The KIPS Transactions:PartB
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• v.17B no.4
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• pp.303-308
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• 2010

In this paper, we propose a medical image registration technique combining the gradient vector flow and modified conditional entropy. The registration is conducted by the use of a measure based on the entropy of conditional probabilities. To achieve the registration, we first define a modified conditional entropy (MCE) computed from the joint histograms for the area intensities of two given images. In order to combine the spatial information into a traditional registration measure, we use the gradient vector flow field. Then the MCE is computed from the gradient vector flow intensity (GVFI) combining the gradient information and their intensity values of original images. To evaluate the performance of the proposed registration method, we conduct experiments with our method as well as existing method based on the mutual information (MI) criteria. We evaluate the precision of MI- and MCE-based measurements by comparing the registration obtained from MR images and transformed CT images. The experimental results show that the proposed method is faster and more accurate than other optimization methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.287-293
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• 2012

This paper presents an efficient image registration method by measuring the similarity, which is based on multi-dimensional intensity fluctuation. Multi-dimensional intensity which considers 4 directions of the image, is applied to reflect more properties in similarity decision. And an intensity fluctuation is also applied to measure comprehensively the similarity by considering a change in brightness between the adjacent pixels of image. The normalized cross-correlation(NCC) is calculated by considering an intensity fluctuation to each of 4 directions. The 5 correlation coefficients based on the NCC have been used to measure the registration, which are total NCC, the arithmetical mean and a simple product on the correlation coefficient of each direction and on the normalized correlation coefficient by the maximum NCC, respectively. The proposed method has been applied to the problem for registrating the 22 face images of 243*243 pixels and the 9 person images of 500*500 pixels, respectively. The experimental results show that the proposed method has a superior registration performance that appears the image properties well. Especially, the arithmetical mean on the correlation coefficient of each direction is the best registration measure.

• Proceedings of the Optical Society of Korea Conference
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• 2005.02a
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• pp.20-21
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• 2005

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.635-637
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• 2013

This paper proposed a new hardware architecture for stereo matching in real time. We minimized the amount of calculation and the number of memory accesses through analyzing calculation of stereo matching. From this, we proposed a new stereo matching calculating cell and a new hardware architecture by expanding it in parallel, which concurrently calculates cost function for all pixels in a search range. After expanding it, we proposed a new hardware architecture to calculate cost function for 2-dimensional region. The implemented hardware can be operated with minimum 250Mhz clock frequence in FPGA environment, and has the performance of 813fps in case of the search range of 64 pixels and the image size of $640{\times}480$.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.128-140
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• 2000

In this paper, we propose a fast block matching algorithm using the mean absolute error (MAE) of neighbor search point and search region reduction. The proposed algorithm is composed of two stages. At the first stage,the search region is divided into nonoverlapped 3$\times$3 areas and MAE of the center point of each area iscalculated. The minimum MAE value of all the calculated MAE's is determined as reference MAE. At thesecond stage, because the possibility that final motion vector exist near the position of reference MAE is veryhigh, we use smaller search region than first stage, And, using the MAE of center point of each area, the lowerbound of rest search point of each area is calculated and block matching process is performed only at the searchpoints that the lower bound is smaller than reference MAE. By doing so, we can significantly reduce thecomputational complexity while keep the increasement of motion estimation error small.