• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2749-2756
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• 2015

Recently, Depending on the quality of data increases, the problem of time-consuming to process the image is raised by being required to accelerate the image processing algorithms, in a traditional CPU and CUDA(Compute Unified Device Architecture) based recognition system for computing speed and performance gains compared to OpenMP When character recognition has been learned by the system to measure the input by the character data matching is implemented in an environment that recognizes the region of the well, so that the font of the characters image learning English alphabet are each constant and standardized in size and character an image matching method for calculating the matching has also been implemented. GPGPU (General Purpose GPU) programming platform technology when using the CUDA computing techniques to recognize and use the four cores of Intel i5 2500 with OpenMP to deal quickly and efficiently an algorithm, than the performance of existing CPU does not produce the rate of four times due to the delay of the data of the partition and merge operation proposed a method of improving the rate of speed of about 3.2 times, and the parallel processing of the video card that processes a result, the sequential operation of the process compared to CPU-based who performed the performance gain is about 21 tiems improvement in was confirmed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.10
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• pp.1114-1120
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• 2009

The conductivity of various electro-threads is analyzed, and the washable electro-thread embroidery UHF RFID tag antennas using the character shape without T-matching structure are designed by adding a T-matching structure. The RFID tag antenna using the electro-thread is easy to be embedded on a cloth as a wearable antenna because it is flexible and different from general copper inlay shape and tape type tag. The embroidery tag antennas are designed with the English alphabet 'F' and the Korea alphabet 'ㄹ' character. Those are easy to be applied to general clothes. The parameters of antennas are optimized and fabricated. The characteristics and the reading range patterns of the tag antennas are measured. The reading ranges of wet tags(tap water, sea water and soapy water) are tested and compared.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.213-221
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• 2022

Intelligent Character Recognition System for Account Payable (ICRS AP) Automation represents the process of capturing text from scanned invoices and extracting the key fields from invoices and storing the captured fields into properly structured document format. ICRS plays a very critical role in invoice data streamlining, we are interested in data like Vendor Name, Purchase Order Number, Due Date, Total Amount, Payee Name, etc. As companies attempt to cut costs and upgrade their processes, accounts payable (A/P) is an example of a paper-intensive procedure. Invoice processing is a possible candidate for digitization. Most of the companies dealing with an enormous number of invoices, these manual invoice matching procedures start to show their limitations. Receiving a paper invoice and matching it to a purchase order (PO) and general ledger (GL) code can be difficult for businesses. Lack of automation leads to more serious company issues such as accruals for financial close, excessive labor costs, and a lack of insight into corporate expenditures. The proposed system offers tighter control on their invoice processing to make a better and more appropriate decision. AP automation solutions provide tighter controls, quicker clearances, smart payments, and real-time access to transactional data, allowing financial managers to make better and wiser decisions for the bottom line of their organizations. An Intelligent Character Recognition System for AP Automation is a process of extricating fields like Vendor Name, Purchase Order Number, Due Date, Total Amount, Payee Name, etc. based on their x-axis and y-axis position coordinates.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.395-404
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• 2013

A pattern matching algorithm plays an important role in traffic identification and classification based on predefined patterns for intrusion detection and prevention. As attacks become prevalent and complex, current patterns are written using regular expressions, called regexes, which are expressed into the deterministic finite automata(DFA) due to the guaranteed worst-case performance in pattern matching process. Currently, because of the increased complexity of regex patterns and their large number, memory-efficient DFA from states reduction have become the mainstay of pattern matching process. However, most of the previous works have focused on reducing only the number of states on a single automaton, and thus there still exists a state blowup problem under the large number of patterns. To solve the above problem, we propose a new state compression algorithm that merges states on multiple automata. We show that by merging states with the same input character on multiple automata, the proposed algorithm can lead to a significant reduction of the number of states in the original DFA by as much as 40.0% on average.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.839-844
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• 2003

This paper presents a method to segment wafer ID marks on poor quality images under uncontrolled lighting conditions of the semiconductor process. The active multiple templates matching method is suggested to search ID areas on wafers and segment them into meaningful regions and it would have been impossible to recognize characters using general OCR algorithms. This active template model is designed by applying a snake model that is used for active contour tracking. Active multiple template model searches character areas and segments them into single characters optimally, tracking each character that can vary in a flexible manner according to string configurations. Applying active multiple templates, the optimization of the snake energy is done using Greedy algorithm, to maximize its efficiency by automatically controlling each template gap. These vary according to the configuration of character string. Experimental results using wafer images from real FA environment are presented.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.1
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• pp.81-87
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• 1994

This paper describes the recognition of the printed Hanguel(Korean Character) using Neural Network. In this study, Neural network is used in only specific classification. Hanguel is classified globally by using template matching. Neural network is learned using the segmented grapheme. The grapheme of Hanguel is segmented using the structural method. Neural network is constructed, which is corresponded to the kind and the shape of graphemes. Each neural network is multi layer perceptron. The learning algorithm is the modified error back propagation using descending epsilon method. With five test character sets, the recognition rate of 94.95% is obtained.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1363-1366
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• 2003

This paper introduces computerized version of Hangout(Korean Language) Standard Pronunciation Rule that can be used in Korean processing systems such as Korean voice synthesis system and Korean voice recognition system. For this purpose, we build Petri net models for each items of the Standard Pronunciation Rule, and then integrate them into the vocal sound conversion table. The reversion of Hangul Standard Pronunciation Rule regulates the way of matching vocal sounds into grammatically correct written characters. This paper presents not only the vocal sound conversion table but also character conversion table obtained by reversely converting the vocal sound conversion table. Making use of these tables, we have implemented a Hangeul character into a vocal sound system and a Korean vocal sound into character conversion system, and tested them with various data sets reflecting all the items of the Standard Pronunciation Rule to verify the soundness and completeness of our tables. The test results shows that the tables improves the process speed in addition to the soundness and completeness.

• Language and Information
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• v.7 no.2
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• pp.81-101
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• 2003

This paper introduces a computerized version of the Korean Standard Pronunciation Rules that can be used in speech engineering systems such as Korean speech synthesis and recognition systems. For this purpose, we build Petri net models for each item of the Standard Pronunciation Rules, and then integrate them into the sound conversion table. The reversion of the Korean Standard Pronunciation Rules regulates the way of matching sounds into grammatically correct written characters. This paper presents not only the sound conversion table but also the character conversion table obtained by reversely converting the sound conversion table. Malting use of these tables, we have implemented a Korean character into a sound system and a Korean sound into the character conversion system, and tested them with various data sets reflecting all the items of the Standard Pronunciation Rules to verify the soundness and completeness of our tables. The test results show that the tables improve the process speed in addition to the soundness and completeness.

• Electronics and Telecommunications Trends
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• v.37 no.5
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• pp.22-32
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• 2022

Optical character recognition is a primary technology required in different fields, including digitizing archival documents, industrial automation, automatic driving, video analytics, medicine, and financial institution, among others. It was created in 1928 using pattern matching, but with the advent of artificial intelligence, it has since evolved into a high-performance character recognition technology. Recently, methods for detecting curved text and characters existing in a complicated background are being studied. Additionally, deep learning models are being developed in a way to recognize texts in various orientations and resolutions, perspective distortion, illumination reflection and partially occluded text, complex font characters, and special characters and artistic text among others. This report reviews the recent deep learning-based text detection and recognition methods and their various applications.

• Korean Journal of Cognitive Science
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• v.3 no.2
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• pp.271-289
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• 1992

In this paper,a cursive on-line Hangul recognition system which permits cursive writing between graphemes is presented.In general,the recognition of cursive Hangul writing has a difficulty of graheme segmentation and a complexity in matching procedure due to the increasing number of character candidates.To manage efficiently these problems,we propose a double segmentation method.Based on this segmentation,a recognition algorithm based on the line segment matching is proposed.Through the experimental result,it is show that the proposed recognition method is suitable for the cursive Hangul writings.