• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.933-939
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• 2012

In general, the three-dimensional(3D) coordinates of the manufactured ship blocks are measured using the laser measuring equipment by ship engineers. But, many deflections between the measured coordinates in manufactured step and the designed coordinates in the design step are occurred because of the measuring process of ship blocks manually. Thus, the ship engineer should conform the consistency between the measured coordinates and the designed coordinates step by step, and it largely causes the loss of manpower and time. In this paper, the automated pattern matching algorithm of 3D coordinates for quality control in ship blocks is suggested in order to solve this problem, and the performance of the algorithm is analyzed using the 3D coordinates simulation software developed by our research laboratory. The coordinates matching rate of the measured coordinates in the single/multi ship block(s) is about 90.2% under the tolerated distance error range is 20~25cm.

• Journal of the Korea Society of Computer and Information
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• v.8 no.3
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• pp.73-79
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• 2003

This paper proposes speaker recognition algorithm which includes both the pitch detection and the fuzzified pattern matching. This study utilizes pitch pattern using a pitch and speech parameter uses binary spectrum. In this paper. makes reference pattern using fuzzy membership function in order to include time variation width for non-utterance time and performs vocal track recognition of common character using fuzzified pattern matching.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.811-814
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• 2003

In this paper, we propose a fast block-matching motion estimation method using the cross pattern and the hexagonal pattern. For the block-matching motion estimation method, full search finds the best motion estimation, but it requires huge search time because it has to check every search point within the search window. The proposed method makes use of the fact that most of motion vectors lie near the center of block. The proposed method first uses the cross pattern to search near the center of block, and then uses the hexagonal pattern to search larger motion vectors. Experimental results show that our method is better than recently proposed search algorithms in terms of mean-square error performance and required search time.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.4
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• pp.120-126
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• 1989

IC chip layout pattern recognition algorithms using image processing techniques are being developed for the automation of manufacturing and inspecting chips. Recognitioin of chip pattern requires feature extraction from nach rrame of chip image adn needs to match the feature data through all frames. In this paper, vertex position and form having layout information are extracted by the feature straightening algorithm, and global coordinates of layout pattern are extracted by the feature straightening algorithm, and global coordinates of layout pattern are obtainnd by vertex form matching from the overlapped area of neighbour frame.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.2021-2030
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• 2012

Premature ventricular contraction(PVC) is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Particularly, in the healthcare system that must continuously monitor patient's situation, it is necessary to process ECG (Electrocardiography) signal in realtime. In other words, the design of algorithm that exactly detects R wave using minimal computation and classifies PVC by analyzing the persons's physical condition and/or environment is needed. Thus, the patient adaptive pattern matching algorithm for the classification of PVC is presented in this paper. For this purpose, we detected R wave through the preprocessing method, adaptive threshold and window. Also, we applied pattern matching method to classify each patient's normal cardiac behavior through the Hash function. The performance of R wave detection and abnormal beat classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.33% in R wave detection and the rate of 0.32% in abnormal beat classification error.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2169-2177
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• 2015

This paper proposes a new pattern matching module to overcome the increased runtime of previous algorithm using RAM, which was designed to overcome cost limitation of hash-based algorithm using CAM (Content Addressable Memory). By adopting Merge FSM algorithm to reduce the number of state, the proposed module contains state block and entry block to use in RAM. In the proposed module, one input string is compared with multiple entry strings simultaneously using entry block. The effectiveness of the proposed pattern matching unit is verified by executing Snort 2.9 rule set. Experimental results show that the number of memory reads has decreased by 15.8%, throughput has increased by 47.1%, while memory usage has increased by 2.6%, when compared to previous methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.27-37
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• 2011

The IDS/IPS(Intrusion Detection/Prevention System) has been widely deployed to protect the internal network against internet attacks. Reducing the packet inspection time is one of the most important challenges of improving the performance of the IDS/IPS. Since the IDS/IPS needs to match multiple patterns for the incoming traffic, we may have to apply the multiple pattern matching schemes, some of which use finite automata, while the others use the shift table. In this paper, we first show that the performance of those schemes would degrade with various kinds of pattern sets and payload, and then propose a hybrid multiple pattern matching scheme which combines those two schemes. The proposed scheme is organized to guarantee an appropriate level of performance in any cases. The experimental results using real traffic show that the time required to do multiple pattern matching could be reduced effectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.228-233
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• 1997

An efficient corner matching algorithm is developed to minimize the amount of calculation. To reduce the amount of calculation, all available information from a corner detector is used to make model. This information has uncertainties due to discretization noise and geometric distortion, and this is represented by fuzzy rule base which can represent and handle the uncertainties. Form fuzzy inference procedure, a matched segment list is extracted, and resulted segment list is used to calculate the transformation between object of model and scene. To reduce the false hypotheses, a vote and re-vote method is developed. Also an auto tuning scheme of the fuzzy rule base is developed to find out the uncertainties of features from recognized results automatically. To show the effectiveness of the developed algorithm, experiments are conducted for images of real electronic components.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.11
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• pp.2711-2722
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• 1993

Most of the current 2-D object recognition systems are model-based. In such systems, the representation of each of a known set of objects are precompiled and stored in a database of models. Later, they are used to recognize the image of an object in each instance. In this thesis, the approach method for the 2-D object recognition is treating an object boundary as a string of structral units and utilizing string matching to analyze the scenes. To reduce string matching time, models are rebuilt by means of fuzzy c-means clustering algorithm. In this experiments, the image of objects were taken at initial position of a robot from the CCD camera, and the models are consturcted by the proposed algorithm. After that the image of an unknown object is taken by the camera at a random position, and then the unknown object is identified by a comparison between the unknown object and models. Finally, the amount of translation and rotation of object from the initial position is computed.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.19-26
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• 2004

In this paper, we suggest a 3D vision inspection method which use only one camera. If we have the database of pattern and can recognize the object, and also estimate the rotated shape of the parts, we can inspect the parts using only one image. We used the 3D database and the 2D geometrical pattern matching, and the rotation transition theory about the algorithm. As the results, we could have the capability of the recognition and inspection of the rotated object through the estimation of rotation an81e. We applied our suggested algorithm to the inspection of typical IC and capacitor, and compared our suggested algorithm with the conventional 2D inspection method and the feature space trajectory method.