• ETRI Journal
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• v.33 no.3
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• pp.401-406
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• 2011

This paper presents a fast block-matching algorithm based on the normalized cross-correlation, where the elimination order is determined based on the gradient magnitudes of subblocks in the current macroblock. Multilevel Cauchy-Schwartz inequality is derived to skip unnecessary block-matching calculations in the proposed algorithm. Also, additional complexity reduction is achieved re-using the normalized cross correlation values for the spatially neighboring macroblock because the search areas of adjacent macroblocks are overlapped. Simulation results show that the proposed algorithm can improve the speed-up ratio up to about 3 times in comparison with the existing algorithm.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.161-164
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• 2010

The study on terrain referenced navigation has been proceeded from 1940s in advanced country with the object of military. In this study, the analysis regarding algorithm developed using cross-correlation matching algorithm and extended Kalman filter and simulation will be introduced. As a result, the standard deviation of position error from cross-correlation matching algorithm has been calculated 34.3m. It meant that the result has stable accuracy on the navigation. However, further study on terrain referenced navigation based on analysis of various topographic characteristics should be performed.

• Convergence Security Journal
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• v.13 no.3
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• pp.9-15
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• 2013

Calculating of matching cost is an important for efficient stereo matching. To investigate the performance of matching process, the concepts of the existing methods are introduced. Also we analyze the performance and merits of them. The simplest matching costs assume constant intensities at matching image locations. We consider matching cost functions which can be distinguished between pixel-based and window-based approaches. The Pixel-based approach includes absolute differences (AD) and sampling-intensitive absolute differences (BT). The window-based approach includes the sum of the absolute differences, the sum of squared differences, the normalized cross-correlation, zero-mean normalized cross-correlation, census transform, and the absolute differences census transform (AD-Census). We evaluate matching cost functions in terms of accuracy and time complexity. In terms of the accuracy, AD-Census method shows the lowest matching error ratio (the best solution). The ZNCC method shows the lowest matching error ratio in non-occlusion and all evaluation part. But it performs high matching error ratio at the discontinuities evaluation part due to blurring effect in the boundary. The pixel-based AD method shows a low complexity in terms of time complexity.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.1
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• pp.1-9
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• 2015

Template matching is used for many applications in image processing. One of the most researched topics is object tracking. Normalized Cross Correlation (NCC) is the basic statistical approach to match images. NCC is used for template matching or pattern recognition. A template can be considered from a reference image, and an image from a scene can be considered as a source image. The objective is to establish the correspondence between the reference and source images. The matching gives a measure of the degree of similarity between the image and the template. A problem with NCC is its high computational cost and occasional mismatching. To deal with this problem, this paper presents an algorithm based on the Sum of Squared Difference (SSD) and an adaptive template matching to enhance the quality of the template matching in object tracking. The SSD provides low computational cost, while the adaptive template matching increases the accuracy matching. The experimental results showed that the proposed algorithm is quite efficient for image matching. The effectiveness of this method is demonstrated by several situations in the results section.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.10-19
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• 2003

As the technical demand for biometrics is increasing, users expect that fingerprint recognition systems are operable with various fingerprint readers. However, current commercial off-the-shelf fingerprint recognition systems are no interoperable due to the lack of standardization in application program interfaces for fingerprint readers. A cross-matching fingerprint recognition system is a person authentication system based on fingerprints and utilizing different types of fingerprint readers. It should be able to overcome variations in fingerprint images acquired by different readers, such as the size, resolution, contrast of images. The purpose of this research is to develop across-matching fingerprint recognition system for fingerprint research of different sensing mechanism. The fingerprint readers tested in this study are optical, semiconductor and thermal sensor modules, and the prpoposed cross-matching system utilizes both a minutiae-based similarity and a ridge count-based similarity in matching fingerprint images acquired by different sensors.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.12
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• pp.659-666
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• 2000

A stereo matching has been an important tool for reconstructing three dimensional terrain. By using stereo matching technique, DEM(Digital Elevaton Map) can be generated by the disparity from a reference image to a target image. Generally disparity map can be evaluated by matching the reference image to the target image and if the role of the reference and the target are interchanged, a different DEM can be obtained. In this paper, we propose a new fusion technique to estimate the optimal DEM by eliminating the false DEM due to occlusion. To detect the false DEM, we utilize two measure of accuracy: self-consistency and cross-correlation score. We test the effectiveness of the proposed methods with a quantitative analysis using simulated images. Experimental result indicate that the proposed methods show 24.4% and 33.1% improvement over either DEM.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.77-87
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• 1996

Existing area-based stereo matching algorithms utilize a single rectangular correlation area for computing cross-correlation between corresponding points in stereo images, and compute disparity by finding the peak in the vicinity of depth discontinuity, since, because of inconstnat disparities around discontinuities, the cross-correlation becomes low in such area. Inthis paper, a new area-based matching strategy is proposed exploiting multiple directional correlation masks instead of a single one. The proposed technique computes multiple cross-covariance functions using each oriented mask. Peaks are detected from each covariance function and the disparity is computed by choosing the location with the highest covariance value. Proposed approach can also be applied to compute disparity gradients without obtaining dense depth data. A number of examples are presented using synthetic and natural stereo images.

• International journal of advanced smart convergence
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• v.6 no.3
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• pp.17-21
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• 2017

In this paper, the service execution accuracy was compared by ontology based rule inference method and machine learning method, and the amount of data at the point when the service execution accuracy of the machine learning method becomes equal to the service execution accuracy of the rule inference was found. The rule inference, which measures service execution accuracy and service execution accuracy using accumulated data and pattern matching on service results. And then machine learning method measures service execution accuracy using cross validation data. After creating a confusion matrix and measuring the accuracy of each service execution, the inference algorithm can be selected from the results.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1251-1260
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• 2018

High-quality sea-ice surface models generated from aerial images can be used effectively as field data for developing satellite-based remote sensing methods but also as analysis data for understanding geometric variations of Arctic sea-ice. However, the lack of texture information on sea-ice surfaces can reduce the accuracy of image matching. In this paper, we analyze the performance of matching cost functions for homogeneous sea-ice surfaces as a part of high-quality sea-ice surface model generation. The matching cost functions include sum of squared differences (SSD), normalized cross-correlation (NCC), and zero-mean normalized cross-correlation (ZNCC) in image domain and phase correlation (PC), orientation correlation (OC), and gradient correlation (GC) in frequency domain. In order to analyze the matching performance for texture changes clearly and objectively, a new evaluation methodology based on the principle of object-space matching technique was introduced. Experimental results showed that it is possible to secure reliability and accuracy of image matching only when optimal search windows are variably applied to each matching point in textureless regions such as sea-ice surfaces. Among the matching cost functions, NCC and ZNCC showed the best performance for texture changes.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.425-428
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• 2008

A new type of cross-coupled planar microwave filter using coupled microstrip square open-loop resonators diplexer pro-posed. A method for the rigorous calculation of the coupling coefficients of basic four pole electric and magnetic coupling structures encountered. Simple empirical models are derived for estimation of the coupling coefficients. Experiments are performed to verify the theory. And a method for diplexer matching is conjugate matching that has characteristic better than open matching method.