• 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 IKEEE
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• v.22 no.1
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• pp.87-92
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• 2018

Like CPUs, regular expression processors that perform regular expression pattern matching using instructions have been proposed recently. Of these, only REMPc provides features for character class matching. In this paper, we propose an architecture for efficient character class matching in a regular expression processor, which use character class bitmap format in a instruction operand field and implement the hard-wired character class comparator for several frequently used character classes. Using the proposed method, most of the character classes used in Snort rule can be represented by an operand or an instruction. Thus, character class matching can be performed more efficiently in the proposed archiecture than in REMPc.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.1015-1019
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• 2010

An extensive research on exact string matching has been done, but there have been few researches on the matching in multi-byte character set texts such as EUC~KR. This paper shows that false matches may occur in multi-byte character set texts such as EUC-KR when using KMP algorithm, and presents a refined KMP algorithm without false matches applying a character-based prefix function. And also, Experimental results show that our algorithm is faster than string matching algorithms of widely used editors, Vim and Emacs, and the existing automata-based algorithm.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.136-144
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• 2002

In this paper, a novel approach that makes use of both shape and color information to retrieve character images in terms of similarity distance from a large-capacity image database or from a streaming image database, in particular, character image logo or trademark. In order to combine both features of completely different characteristics bipartite matching has been employed in computing similarity distance, The proposed method turned out to bealso very effective in matching natural object or human-drawn images whose shape varies substantially.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.521-526
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• 2005

In this Paper, we propose a keyword spotting system as an alternative to searching system for poor quality Korean document images and compare the Proposed system with an OCR-based document retrieval system. The system is composed of character segmentation, feature extraction for the query keyword, and word-to-word matching. In the character segmentation step, we propose an effective method to remove the connectivity between adjacent characters and a character segmentation method by making the variance of character widths minimum. In the query creation step, feature vector for the query is constructed by a combination of a character model by typeface. In the matching step, word-to-word matching is applied base on a character-to-character matching. We demonstrated that the proposed keyword spotting system is more efficient than the OCR-based one to search a keyword on the Korean document images, especially when the quality of documents is quite poor and point size is small.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.4
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• pp.54-64
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• 1999

This paper proposes an efficient handwritten English word recognition scheme which can be applied practical applications. To effectively use the lexicon which is available in most handwriting related applications, the lexicon entries are introduced in the early stage of the recognition. Dynamic programming is used for matching between over-segmented character segments and letters in the lexicon entries. Character segmentation statistics which can be obtained while the training is being performed are used to adjust the matching window size. Also, the matching results between the character segments and the letters in the lexicon entries are cached to avoid repeat of the same computation. In order to verify the effectiveness of the proposed methods, several experiments were performed using thousands of word images with various writing styles. The results show that the proposed methods significantly improve the matching speed as well as the accuracy.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.24-30
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• 1993

In this paper, a new method is proposed to recognize a character from its similar characters, which are selected by pattern matching method in Korean character recognition. This new method, which couples the merits of already suggested methods, can choose the character to be in the candidate set and discriminate it from the others correctly. To evaluate performance of this algorithm, we used 15 kinds of different laser printer fonts and obtained about 97% of recognition rate.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.1
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• pp.29-37
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• 1989

This paper presents an application of the extended DP matching method to the on-line recognition of cursive Hangeul (Korean characters). We decrease the number of matching's objects by performing rough classification matching which makes the best use of features in the first and the last segment of Hangeul. By adding the extraction function of the basic character patterns to DP matching method, we try to calculate precisely the difference among Hangeul. The extraction of the basic character patterns is done by examining the features of segments in character. Applying the extended DP matching method to the on-line recognition of cursive Hangeul, absorption of writing motion and stable separation of strokes can be performed with flexibility.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.2
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• pp.180-195
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• 1991

In this paper, we studied on new method of recognition using structural information to recognize character pattern in orginal shape of Hangeul. First, for the purpose of knowing location of character in input image. it processed Making block. Second, after we investigated. whether vertical vowel exited or not in character image accordingly the center of gravity of Hangeul. each character was classified into Type of Hangeul by searching location and length for horizontal vowel and short pole. Last, we processed it by means of template matching which calculate Uclid's distance on each Jaso in accordance to type classified. This paper made an experiment on 2350 characters and obtained 98.3% classifing rate and 95.2% recognizing rate.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.297-297
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• 2000

This paper proposed character recognition method by using DB Matching and Artificial Neural Network at the Gerber files. Gerber files are file for make PCB. But we also use the file to a program of extraction PCB position data. If the Gerber file recognized a character, the extraction PCB position data will be faster and also when the recognition rate is high, it can be possible to automatic extraction. We apply to the construction PCB Gerber file program and Simulation results are presented to verify the usefulness of the method.