• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.171-176
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• 2004

Image matching is fundamental process in photogrammetry and computer vision to identify and to measure corresponding features on the multiple images. Uniqueness of the matching entities and robustness of the algorithm are the key issues that have influence on quality of the matching result. The optimal solution could be obtained by utilizing appropriate matching entities in the first place. In this study, candidate matching points were extracted by interest operator, and an area-based matching method was applied with characteristics of the gray value distribution as the matching entities. The characteristic information is based on the concept of "intrinsic image" (or parameter image). The information was utilized as additional and/or complementary matching entities. Matching on interest points with the characteristic information resulted in high quality of matching because matching windows were created with surrounding pixels of the interest points that contain distinct and unique features. The experiment shows that matching quality and reliability increase by exploiting interest operator, and the characteristic information has potential to be matching entity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.711-725
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• 2013

A heuristic with multi-byte suffix matching plays an important role in real pattern matching algorithms. By skipping many characters at a time in the process of comparing a given pattern with the text, the pattern matching algorithm based on a heuristic with multi-byte suffix matching shows a faster average search time than algorithms based on deterministic finite automata. Based on various experimental results and simulations, the previous works show that the pattern matching algorithms with multi-byte suffix matching performs well. However, there have been limited studies on the mathematical model for analyzing the performance in a standard manner. In this paper, we propose a new probabilistic model, which evaluates the performance of a heuristic with multi-byte suffix matching in an average-case search. When the theoretical analysis results and experimental results were compared, the proposed probabilistic model was found to be sufficient for evaluating the performance of a heuristic with suffix matching in the real pattern matching algorithms.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.247-254
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• 2011

This paper presents a method of sonar grid map matching for topological place recognition. The proposed method provides an effective rotation invariant grid map matching method. A template grid map is firstly extracted for reliable grid map matching by filtering noisy data in local grid map. Using the template grid map, the rotation invariant grid map matching is performed by Ring Projection Transformation. The rotation invariant grid map matching selects candidate locations which are regarded as representative point for each node. Then, the topological place recognition is achieved by calculating matching probability based on the candidate location. The matching probability is acquired by using both rotation invariant grid map matching and the matching of distance and angle vectors. The proposed method can provide a successful matching even under rotation changes between grid maps. Moreover, the matching probability gives a reliable result for topological place recognition. The performance of the proposed method is verified by experimental results in a real home environment.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.208-217
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• 2012

This paper presents two adaptive fingerprint matching methods. First, we experiment an adaptive threshold selection of 1:N matching system in order to raise the reliability of the matching score. Second, we propose a adaptive threshold selection using fitting algorithm for high speed matching. The experiment was conducted on the NITZEN database, which has 5247 samples. Consequently, this paper shows that our suggested method can perform 1.88 times faster matching speed than the bidirectional matching speed. And, we prove that FRR of our suggested method decreases 1.43 % than that of the unidirectional matching.

• Korean Journal of Remote Sensing
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• v.13 no.2
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• pp.121-132
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• 1997

This paper describes the development of a stereo matching algorithm for extracting Digital Elevation Model(DEM) from satellite images. This matching algorithm is based on a non-linear least squares correlation estimation but has improved matching speed. The algorithm consists of three steps: matching execution, matching control and matching optimization. Each is described. The performance of the presented algorithm is quantitatively analyzed with experiments on matching probability, matching speed and matching convergence radius.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.8
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• pp.44-53
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• 1992

In this paper, a matching method is proposed to improve the correct matching rate in stereo correspondence matching in which the fingerprint of zero-crossing points on the scale-space is used as the robust matching feature. The dynamic programming, which is appropriate for the fingerprint feature, is introduced for correspondence matching. We also improve the matching rate by using the post-processing for correcting mismatched points. In simulation, we apply the proposed algorithm to the synthetic and real images and obtain good matching results.

• 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 KIISE
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• v.42 no.10
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• pp.1280-1285
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• 2015

Many hardware-based regular expression matching architectures are proposed for high performance matching. In particular, regular expression processors such as ReCPU and SMPU perform pattern matching in a similar approach to that used in general purpose processors, which provide the flexibility when updating patterns. However, these processors are inefficient in performing class matching since they do not provide character class matching capabilities. This paper proposes an instruction set and architecture of a regular expression matching processor, which can support character class matching. The proposed processor can efficiently perform character class matching since it includes character class, character range, and negated character class matching capabilities.

• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.69-76
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• 2011

Matching customers becomes the key function in on-line mediate services. There are two matching methods: one-directional matching that requires requests from one side(e,g., information searching), bi-directional matching that considers requests from both sides. Previous bi-directional matching has difficulties of getting the interests explicitly and service collapse problems when the opposite side do not put responding interests. This paper attempts to automate the inputs of interests for bi-directional matching by calculating the interests with fuzzy matching algorithm for optimization. The results of the proposed Bi-directional Fuzzy Matching(BDFM) algorithm told that the job placement accuracy of employment information matching results is over 95%. And, BDFM gives statically significant positive effect for motivating the employment activities when analyzed the effect after completing the implementation.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.2
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• pp.251-254
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• 2016

An energy-efficient object matching accelerator is proposed for mobile object recognition based on matching prediction scheme. Conventionally, vocabulary tree has been used to save the external memory bandwidth in object matching process but involved massive internal memory transactions to examine each object in a database. In this paper, a novel object matching accelerator is proposed based on matching predictions to reduce unnecessary internal memory transactions by mitigating non-target object examinations, thereby improving the energy-efficiency. Experimental results show a 26% reduction in power-delay product compared to the prior art.