• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.110-116
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• 2014

Pattern matching algorithms are widely used in computer security systems such as computer networks, ubiquitous networks, sensor networks, and so on. However, the advances in information technology causes grow on the amount of data and increase on the computation complexity of pattern matching processes. Therefore, there is a strong demand for a novel high performance pattern matching algorithms. In light of this fact, this paper newly proposes a suffix tree based pattern matching algorithm. The suffix tree is constructed based on the suffix values of all patterns. Then, the shift nodes which informs how many characters can be skipped without matching operations are added to the suffix tree in order to boost matching performance. The proposed algorithm reduces memory usage on the suffix tree and the amount of matching operations by the shift nodes. From the performance evaluation, our algorithm achieved 24% performance gain compared with the traditional algorithm named as Wu-Manber.

• Korean Journal of Remote Sensing
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• v.23 no.4
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• pp.273-285
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• 2007

Most stereo matching methods use intensity values in small image patches to measure the correspondence between two points. If the noisy pixels are used in computing the corresponding point, the matching performance becomes low. For this reason, the noise plays a critical role in determining the matching performance. In this paper, we propose a method for combining intensity and edge filters robust to the noise in order to improve the performance of stereo matching using high resolution satellite imagery. We used intensity filters such as Mean, Median, Midpoint and Gaussian filter and edge filters such as Gradient, Roberts, Prewitt, Sobel and Laplacian filter. To evaluate the performance of intensity and edge filters, experiments were carried out on both synthetic images and satellite images with uniform or gaussian noise. Then each filter was ranked based on its performance. Among the intensity and edge filters, Median and Sobel filter showed best performance while Midpoint and Laplacian filter showed worst result. We used Ikonos satellite stereo imagery in the experiments and the matching method using Median and Sobel filter showed better matching results than other filter combinations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.1-8
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• 1994

In this paper, we propose an efficient two-step pattern matching method which promises shape distortion-tolerant recognition of handwritten of handwritten Hangul syllables. In the first step, nonlinear shape normalization is carried out to compensate for global shape distortions in handwritten characters, then a preliminary classification based on simple pattern matching is performed. In the next step, nonlinear pattern matching which achieves best matching between input and reference pattern is carried out to compensate for local shape distortions, then detailed classification which determines the final result of classification is performed. As the performance of recognition systems based on pattern matching methods is greatly effected by the quality of reference patterns. we construct reference patterns by combining the proposed nonlinear pattern matching method with a well-known averaging techniques. Experimental results reveal that recognition performance is greatly improved by the proposed two-step pattern matching method and the reference pattern construction scheme.

• IE interfaces
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• v.23 no.2
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• pp.164-175
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• 2010

In logistics e-marketplaces, brokerage agents intermediate empty vehicles and freights registered by car owners and shippers. In the previous research, we proposed constant periodic/fixed matching algorithms for the logistics brokerage agents with the objective of minimizing the total transportation lead time and the transportation due date tardiness of freights(Jeong, 2004; Jeong, 2007). However, the constant type algorithms cannot consider changes in the balance status of an e-marketplace, i.e. the difference between the numbers of freights and vehicles to wait for matching, because they use non-changing matching periods and amounts. In this paper, we propose variable type algorithms for the logistics brokerage agent, in which the matching periods and amounts are changed continuously by considering the balance status between the freights and vehicles. In order to compare performance of the variable type algorithms to the previous constant type algorithms, we carried out computational experiments on various problem instances. The results show that the variable type algorithms give better performance than the constant type algorithms. We can expect that the logistics brokerage agents can improve their performance by using the proposed variable periodic/fixed matching algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.105-110
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• 2015

This paper relates with the eualization performance of Constellation Matching-MMA (CM-MMA) in order to the consists of optimum receiver for the minimization of intersymbol interference and additive noise effects that is occurs in the nonlinear communication channel. The error signal were obtained that combines the Constellation Matching technique that inserts the zero point between the signal point of equalizer for improving the residual isi and convergence speed compared to the currently used MMA algorithm. In the initial state of adaptive equalization, it depends on the MMA characteristics mainly. And in the steady state, it depends on the CM characteristics mainly. In order to analyzing the equalization performance, the output signal constellation, residual isi, maximum distortion, MSE and SER were applied, then it were compared with the present MMA algorithm. As a result of computer simulation, the CM-MMA has more better performance in the every performance index, and it was also confirmed that the constellation matching effect can be obtained in the greater than 20dB signal to noise ratio.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2225-2227
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• 1998

An efficient stereo matching method with variable matching weights is proposed. The edge segment-based stereo matching has been shown to be efficient method. The method includes 5 matching factor with different weights. The ordinary matching weights are not always adequate for every image. Employing different weight sets depending on the complexity shows better matching performance. In this paper, an evaluation criterion for complexity is suggested and the experimental results with the proposed method is shown.

• Journal of the Semiconductor & Display Technology
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• v.8 no.4
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• pp.95-100
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• 2009

This paper presents an efficient disparity matching, using sum of absolute difference (SAD) and dynamic programming (DP) algorithm. This algorithm makes use of one of area-based algorithm which is the absolute sum of the pixel difference corresponding to the window size. We use the information of the right eye brightness (B) and the left eye brightness to get an best matching results and apply the results to the left eye image using the window go by the brightness of the right eye image. This is that we can control the brightness. The major feature of this algorithm called SAD+DP+B is that although Root Mean Square (RMS) performance is slightly less than SAD+DP, due to comparing original image, its visual performance is increased drastically for matching the disparity map on account of its matching compared to SAD+DP. The simulation results demonstrate that the visual performance can be increased and the RMS is competitive with or slightly higher than SAD+DP.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.76-82
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• 2017

An image hash, a discriminative and robust summary of an image, should be robust against quality-preserving signal processing steps, while being pairwise independent for perceptually different inputs. In order to improve the hash matching performance, this paper proposes a probabilistic dissimilarity matching. Instead of extracting the binary hash from the query image, we compute the probability that the intermediate hash vector of the query image belongs to each quantization bin, which is referred to as soft quantization binning. The probability is used as a weight in comparing the binary hash of the query with that stored in a database. A performance evaluation over sets of image distortions shows that the proposed probabilistic matching method effectively improves the hash matching performance as compared with the conventional Hamming distance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.1
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• pp.101-109
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• 2011

This paper describes the attempts to improve the performance of an image matching method for multiple image. Typically, matching between two images is performed by using correlation between a reference and corresponding images. The proposed multiple image matching algorithm performs matching in an object space, chooses the image closest to the true vertical image as a reference image, calculates the correlation based on the chosen reference image. The algorithm also detects occluded regions automatically and keep them from matching. We could find that it is possible to create high quality DEM by this method, regardless of the location of image. From the performance improvement experiments through the occlusion detection, we could confirm the possibility of a more accurate representation of 3D information.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.3
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• pp.11-25
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• 2009

Fingerprint sample quality is one of major factors influencing the matching performance of fingerprint recognition systems. The error rates of fingerprint recognition systems can be decreased significantly by removing poor quality fingerprints. The purpose of this paper is to assess the effectiveness of individual sample quality measures on the performance of minutiae-based fingerprint recognition algorithms. Initially, the authors examined the various factors that influenced the matching performance of the minutiae-based fingerprint recognition algorithms. Then, the existing measures for fingerprint sample quality were studied and the more effective quality measures were selected and compared with two image quality software packages, (NFIQ from NIST, and QualityCheck from Aware Inc.) in terms of matching performance of a commercial fingerprint matcher (Verifinger 5.0 from Neurotechnologija). The experimental results over various Fingerprint Verification Competition (FVC) datasets show that even a single sample quality measure can enhance the matching performance effectively.