• Journal of the Korea Computer Industry Society
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• v.2 no.3
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• pp.285-296
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• 2001

This Paper develops the Hanguel character learning system for elementary school students and foreigners. Standard character pattern is selected and DB is consructed for model by feature extraction. For this, performance of pre-processing independent of environments, feature extraction and simility functions are defined. Finally, beauty evaluation is done by matching between input character pattern written by elementary school students or foreigners and standard character pattern. It is possible for this system to extend the specific character font learning from selecting the specific standard character pattern. Also the effectiveness of this parer is demonstrated by several experiments.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3155-3163
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• 2000

In the recognitionsystem of car license plate, it is very important to extract the character from the license plate and recognize the extrated character. In this paper, I use the adaptive algorithm to recognize the charactor of licensse plate image. The adaptive algorithm is compounded of thinning algorithm template matching,algarthm, vector algorithm and so on. The adaptive algorithm was used to recognize the character from license image. In the result of expenment, character recognition is about up to 90% with the adaptive algorithm for the character region.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.8
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• pp.1-6
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• 1992

This paper proposed a neural computer architecture for the learning of script character pattern recognition categories. Oriented filter with complex cells preprocess about the input script character, abstracts contour from the character. This contour normalized and inputed to the ART. Top-down attentional and matching mechanisms are critical in self-stabilizing of the code learning process. The architecture embodies a parallel search scheme that updates itself adaptively as the learning process unfolds. After learning ART self-stabilizes, recognition time does not grow as a function of code complexity. Vigilance level shows the similarity between learned patterns and new input patterns. This character recognition system is designed to adaptable. The simulation of this system showed satisfied result in the recognition of the hand written characters.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.1025-1031
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• 2000

Pre-existing pattern recognition techniques, in the case of character recognition, have limited on the application field. But CAI character learning system and writer's recognition system are very important parts. The application field of pre-existing system can be expanded in the content that the learning of characters and the recognition of writers in the proposed paper. In order to achieve these goals, the development contents are the following: Firstly, pre-processing method by understanding the image structure is proposed, secondly, recognition of characters are accomplished b the histogram distribution characteristics. Finally, similarity measure functions are defined from standard character pattern for matching of the input character pattern. Also the effectiveness of this system is demonstrated by experimenting the standard primitive image.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.131-134
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• 1995

A three dimensional fractal coding with a perceptually enhanced matching is proposed. Since most of medical images (e.g. computed tomography or magnetic resonance image) have three dimensional character, the searching region is extended to adjacent slices. For perceptually enhanced matching, a high frequency booster filter is used for prefiltering of the original image, and the least mean square error matching is applied to this edge enhanced image rather than the original image. From the simulation with the magnetic resonance images ($255{\times}255$, 8bits/pixel). the proposed algorithm provides excellent image quality with compression rations higher than 10. Compared to existing fractal coding the algorithm also provides better subjective image quality with higher compression ratio.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.4
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• pp.116-129
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• 1993

This paper proposes an on-line Recognition scheme of cursive Korean characters based on the DP matching and fuzzy concept. The proposed algorithm, invariant to rotation and size, reduces greatly the computational requirement of dynamic programming by matching phonemes rather than character patterns, where the angle difference and the ration of lengths between input and reference patterns are adopted as matching features. The correct matching of poorly written cursive characters becomes possible by introducing the fuzzy concept in representing the features of phonemes and the ralative position between adjacent phonemes. Computer simulation results are observed to show the effectiveness of the proposed algorithm.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.135-141
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• 2013

String matching is one of the key algorithms in network security and many areas could be benefit from a faster string matching algorithm. Based on the most efficient string matching algorithm in sual applications, the Boyer-Moore (BM) algorithm, a novel algorithm called RQS is proposed. RQS utilizes an improved bad character heuristic to achieve bigger shift value area and an enhanced good suffix heuristic to dramatically improve the worst case performance. The two heuristics combined with a novel determinant condition to switch between them enable RQS achieve a higher performance than BM both under normal and worst case situation. The experimental results reveal that RQS appears efficient than BM many times in worst case, and the longer the pattern, the bigger the performance improvement. The performance of RQS is 7.57~36.34% higher than BM in English text searching, 16.26~26.18% higher than BM in uniformly random text searching, and 9.77% higher than BM in the real world Snort pattern set searching.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.1
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• pp.43-54
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• 2000

Character-based trademarks constitute 90% of registered trademarks at the Korean Patent Office. This paper proposes a method to improve the precision rate when for similar trademarks in such systems. The proposed method first calculates the similarity measure by an image processing. The method has been implemented and merged with the existing device-mark retrieval system to improve precision rate by 16.2% compared to other approximate matching methods.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.166-174
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• 1994

This paper presents the algorithm of an on-line cursive Hangeul recognition by means of the DP matching with structural information. In the proposed method, the penalty represents the similarity between input character and reference character. The penalty is dynamically computed with types of strokes, directions of strokes, and the length rations of fragment during the process that searchs for an optimal path using 3$\times$3 matrix. As the result, this method can be exactly matched for even greatly deformed characters. The computer simulation shows that the proposed algorithm can be utilized in recognizing cursive Hangeul as well as correct Hangeul.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.661-680
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• 2016

The vehicle license plate recognition (VLPR) system analyzes and monitors the speed of vehicles, theft of vehicles, the violation of traffic rules, illegal parking, etc., on the motorway. The VLPR consists of three major parts: license plate detection (LPD), license plate character segmentation (LPCS), and license plate character recognition (LPCR). This paper presents an efficient method for the LPCS and LPCR of Korean vehicle license plates (LPs). LP tilt adjustment is a very important process in LPCS. Radon transformation is used to correct the tilt adjustment of LP. The global threshold segmentation method is used for segmented LP characters from two different types of Korean LPs, which are a single row LP (SRLP) and double row LP (DRLP). The cross-correlation matching method is used for LPCR. Our experimental results show that the proposed methods for LPCS and LPCR can be easily implemented, and they achieved 99.35% and 99.85% segmentation and recognition accuracy rates, respectively for Korean LPs.