• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1667-1679
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• 2010

This thesis proposes an adaptive variable-sized matching window method using the characteristic points of the image and a method to increase the reliability of the cross-consistency check to raise the correctness of the final disparity image. The proposed adaptive variable-sized window method segments the image with the color information, finds the characteristic points in each segmented image, and varies the size of the matching window according to the existence of the characteristic points inside the window. Also the proposed cross-consistency check method processes the two cases with the cost values corresponding to the best disparity and the second-best disparity: when the cost values themselves are too large and when the difference between the two cost values are too small. The two proposed methods were experimented with the four test images provided by the Middleburry site. As the results from the experiments, the proposed adaptive variable-sized matching window method decreased up to 18.2% of error ratio and the proposed cross-consistency check method increased up to 7.4% of reliability.

• Journal of Broadcast Engineering
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• v.18 no.5
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• pp.669-679
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• 2013

This paper proposed a new VLSI (Very Large Scale Integrated Circuit) 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 (Field Programmable Gate Array) environment, and has the performance of 805fps in case of the search range of 64 pixels and the image size of $640{\times}480$.

• Communications for Statistical Applications and Methods
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• v.26 no.5
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• pp.507-517
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• 2019

Statistical matching is a method of combining multiple sources of data that are extracted or surveyed from the same population. It can be used in situation when variables of interest are not jointly observed. It is a low-cost way to expect high-effects in terms of being able to create synthetic data using existing sources. In this paper, we propose the several statistical micro matching methods using a multinomial logistic regression model when all variables of interest are categorical or categorized ones, which is common in sample survey. Under conditional independence assumption (CIA), a mixed statistical matching method, which is useful when auxiliary information is not available, is proposed. We also propose a statistical matching method with auxiliary information that reduces the bias of the conventional matching methods suggested under CIA. Through a simulation study, proposed micro matching methods and conventional ones are compared. Simulation study shows that suggested matching methods outperform the existing ones especially when CIA does not hold.

• Journal of IKEEE
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• v.28 no.1
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• pp.65-71
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• 2024

This paper proposes a neural network that can reduce the number of parameters while reducing matching errors in occluded regions to increase the accuracy of depth maps in stereo matching. Stereo matching-based object recognition is utilized in many fields to more accurately recognize situations using images. When there are many objects in a complex image, an occluded area is generated due to overlap between objects and occlusion by background, thereby lowering the accuracy of the depth map. To solve this problem, existing research methods that create context information and combine it with the cost volume or RoIselect in the occluded area increase the complexity of neural networks, making it difficult to learn and expensive to implement. In this paper, we create a depthwise seperable neural network that enhances regional feature extraction before cost volume generation, reducing the number of parameters and proposing a neural network that is robust to occlusion errors. Compared to PSMNet, the proposed neural network reduced the number of parameters by 30%, improving 5.3% in color error and 3.6% in test loss.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.6
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• pp.11-20
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• 1997

This paper proposes a modified dynamic programming for finding the correspondence between right and left images. A dynamic programming is based on the intensity of images for stereo matching. But htis method is intended to mismatch at uniformed intensity region. To reduce thd mismatching, the stereo images are segmented to various regions with respective uniform intensity, and the different cost function has applied to the segmented region during the dynamci programming. Cost function costains jump cost. And jump cost included two parameter .alpha. and .beta. which have influence on minimum cost path. Experimental results show that the 3D shape of some stereo pairs cna be finely obtained by this proposed algorithm.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.708-710
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• 2004

This paper studies a multirate sampled-data control for LTI systems by using the digital redesign (DR) method. In this note, to well tackle the problem associated with both the state matching and the stabilization, our nobel strategy is to minimize the linear quadratic cost function. The main features of the proposed method are that i) the delta-operator-based descretization method is applied to improve the state-matching performance in the fast sampling limit and/or the large input multiplicity; ii) the proposed multirate control scheme can improve the state-matching performance in the long sampling limit; iii) some sufficient conditions that guarantee the stability of the closed-loop discrete-time system and provide a guarantee cost for the cost function can be formulated in the LMIs format; and iv) an optimal sampled-data controller in the sense of minimizing the upper bound of the cost function is also given by means of an LMI optimization procedure.

• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.902-915
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• 2011

Recently in the area-based stereo matching field, Adaptive Support-Weight (ASW) method that weights matching cost adaptively according to the luminance intensity and the geometric difference shows promising matching performance. However, ASW requires more computational cost than other matching algorithms do and its real-time implementation becomes impractical. By applying Integral Histogram technique after approximating to the Bilateral filter equation, the computational time of ASW can be restricted in constant time regardless of the support window size. However, Integral Histogram technique causes loss of the matching accuracy during approximation process of the original ASW equation. In this paper, we propose a novel algorithm that maintains the ASW algorithm's matching accuracy while reducing the computational costs. In the proposed algorithm, we propose Sub-Block method that groups the pixels within the support area. We also propose the method adjusting the disparity search range depending on edge information. The proposed technique reduces the calculation time efficiently while improving the matching accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.8
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• pp.1703-1708
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• 2005

This paper proposes a modified block matching algorithm which reduces an amount of matching computation by using only pixels contributing greatly to block matching. In consideration of algorithm implementation and additional informatirm, the proposed algorithm divides a matching block into sub-blocks, selects some sub-blocks using their complexities, and execute the block mating with them. Simulation results show that the proposed algorithm performs a valid block matching, diminishing computation cost.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.483-488
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• 2019

This study first examines whether the high matching principle reduces the cost of equity, and then examines the effect on discretionary accruals and capital cost. According to previous studies, the higher the response to revenue cost, the higher the earnings quality. The higher the quality of earnings, the lower the information risk, and the lower the information risk, the lower the capital cost of enterprise. Discretionary accruals can play two roles in opposing each other. One is that managers use the discretionary accruals to provide private information about the future of the corporation to the market, thus enhancing the usefulness of the earnings. The other is that managers can use the discretionary accruals opportunistically to distort earnings and provide misinformed information to investors, thus reducing the usefulness of earnings. The results of this study represents that the higher the responding to the revenue cost, the less the cost of equity. In the case of firms with high revenue response, we examine whether discretionary accruals reduce the cost of equity capital. As a result of the study, the higher the responding to the revenue cost, the lower the cost of equity capital. Companies with higher matching principle have been shown to reduce their capital costs by using discretionary accruals.

• ETRI Journal
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• v.35 no.6
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• pp.1011-1020
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• 2013

In this paper, we present a method for obtaining a high-quality 3D depth. The advantages of active pattern projection and passive stereo matching are combined and a system is established. A diffractive optical element (DOE) is developed to project the active pattern. Cross guidance (CG) and auto guidance (AG) are proposed to perform the passive stereo matching in a stereo image in which a DOE pattern is projected. When obtaining the image, the CG emits a DOE pattern periodically and consecutively receives the original and pattern images. In addition, stereo matching is performed using these images. The AG projects the DOE pattern continuously. It conducts cost aggregation, and the image is restored through the process of removing the pattern from the pattern image. The ground truth is generated to estimate the optimal parameter among various stereo matching algorithms. Using the ground truth, the optimal parameter is estimated and the cost computation and aggregation algorithm are selected. The depth is calculated and bad-pixel errors make up 4.45% of the non-occlusion area.