• Title/Summary/Keyword: OCR

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A Study on the Interference in Single Frequency Network and On Channel Repeater (SFN 및 OCR의 간섭영향에 관한 연구)

  • 최성웅;이형수;오우진
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.10a
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    • pp.737-740
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    • 2003
  • SFN (Single Frequency Network) and OCR (On Channel Repeater) are often considered for the efficiency of frequency allotment in digital TV. In this paper, we discuss the performance and evaluate some coverage criterions for SFN and OCR. Also, we propose MATLAB simulator for coverage planning and estimation.

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Development of the automated gate system based on RFID/OCR in a container terminal (RFID/OCR 기반의 자동화 게이트시스템 개발)

  • Choi, Hyung-Rim;Park, Byung-Joo;Shin, Joong-Jo;Keceli, Yavuz;Lee, Jung-Hee
    • Journal of Korea Society of Industrial Information Systems
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    • v.12 no.2
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    • pp.37-48
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    • 2007
  • In order to become a mega hub port, major ports all over the world are making every effort to enhance their productivity through efficiency of internal operation and introduction of the state-of-the-art technologies. They are not only installing various kinds of high-technology equipments but also introducing advanced technologies for the development of an effective gate system. Recently thanks to the appearance of RFID (radio frequency identification) and OCR (optical character recognition) technology, major container terminals are stewing up the automation of truck and container identification at the container luminal gate. This study aim to develop an automated gate system for identification task based on RFID and OCR technology. It will make mn effective gate operations in a container terminal.

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OCR evaluation of cohesionless soil in centrifuge model using shear wave velocity

  • Cho, Hyung Ik;Sun, Chang Guk;Kim, Jae Hyun;Kim, Dong Soo
    • Geomechanics and Engineering
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    • v.15 no.4
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    • pp.987-995
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    • 2018
  • In this study, a relationship between small-strain shear modulus ($G_{max}$) and overconsolidation ratio (OCR) based on shear wave velocity ($V_S$) measurement was established to identify the stress history of centrifuge model ground. A centrifuge test was conducted in various centrifugal acceleration levels including loading and unloading sequences to cause various stress histories on centrifuge model ground. The $V_S$ and vertical effective stress were measured at each level of acceleration. Then, a sensitivity analysis was conducted using testing data to ensure the suitability of OCR function for the tested cohesionless soils and found that OCR can be estimated based on $V_S$ measurements irrespective of normally-consolidated or overconsolidated loading conditions. Finally, the developed $G_{max}$-OCR relationship was applied to centrifuge models constructed and tested under various induced stress-history conditions. Through a series of tests, it was concluded that the induced stress history on centrifuge model by compaction, g-level variation, and past overburden load can be analysed quantitatively, and it is convinced that the OCR evaluation technique will contribute to better interpret the centrifuge test results.

Development of Intelligent OCR Technology to Utilize Document Image Data (문서 이미지 데이터 활용을 위한 지능형 OCR 기술 개발)

  • Kim, Sangjun;Yu, Donghui;Hwang, Soyoung;Kim, Minho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.212-215
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    • 2022
  • In the era of so-called digital transformation today, the need for the construction and utilization of big data in various fields has increased. Today, a lot of data is produced and stored in a digital device and media-friendly manner, but the production and storage of data for a long time in the past has been dominated by print books. Therefore, the need for Optical Character Recognition (OCR) technology to utilize the vast amount of print books accumulated for a long time as big data was also required in line with the need for big data. In this study, a system for digitizing the structure and content of a document object inside a scanned book image is proposed. The proposal system largely consists of the following three steps. 1) Recognition of area information by document objects (table, equation, picture, text body) in scanned book image. 2) OCR processing for each area of the text body-table-formula module according to recognized document object areas. 3) The processed document informations gather up and returned to the JSON format. The model proposed in this study uses an open-source project that additional learning and improvement. Intelligent OCR proposed as a system in this study showed commercial OCR software-level performance in processing four types of document objects(table, equation, image, text body).

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Real-time Character Detection System Using EAST Model and OCR (EAST 모델과 OCR을 이용한 실시간 문자 탐지 시스템)

  • Ye-Jun Choi;Mikyeong Moon
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.683-684
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    • 2023
  • 웹페이지나 디지털 문서에는 특정 단어나 특정 문구를 검색하는 기능이 있다. 인쇄된 도서나 참고서 등과 같은 인쇄물에는 실시간으로 특정 단어나 특정 문구를 찾는 기능이 없어 어려움을 겪는 경우가 많다. 본 논문에서는 텍스트를 감지(Detection)하는 EAST 모델과 텍스트를 인식(Recognition)하는 EasyOCR을 활용한 실시간 문자 탐지 시스템의 개발내용에 대해 기술한다. 이 시스템을 통해 사용자는 인쇄물에서 실시간으로 원하는 단어나 문구를 찾아 필요한 정보를 빠르게 읽는 것에 효과적일 것을 기대한다.

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Multi-modal Image Processing for Improving Recognition Accuracy of Text Data in Images (이미지 내의 텍스트 데이터 인식 정확도 향상을 위한 멀티 모달 이미지 처리 프로세스)

  • Park, Jungeun;Joo, Gyeongdon;Kim, Chulyun
    • Database Research
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    • v.34 no.3
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    • pp.148-158
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    • 2018
  • The optical character recognition (OCR) is a technique to extract and recognize texts from images. It is an important preprocessing step in data analysis since most actual text information is embedded in images. Many OCR engines have high recognition accuracy for images where texts are clearly separable from background, such as white background and black lettering. However, they have low recognition accuracy for images where texts are not easily separable from complex background. To improve this low accuracy problem with complex images, it is necessary to transform the input image to make texts more noticeable. In this paper, we propose a method to segment an input image into text lines to enable OCR engines to recognize each line more efficiently, and to determine the final output by comparing the recognition rates of CLAHE module and Two-step module which distinguish texts from background regions based on image processing techniques. Through thorough experiments comparing with well-known OCR engines, Tesseract and Abbyy, we show that our proposed method have the best recognition accuracy with complex background images.

An Adaptive Setting Method for the Overcurrent Relay of Distribution Feeders Considering the Interconnected Distributed Generations

  • Jang Sung-Il;Kim Kwang-Ho;Park Yong-Up;Choi Jung-Hwan;Kang Yong-Cheol;Kang Sang-Hee;Lee Seung-Jae;Oshida Hideharu;Park Jong-Keun
    • KIEE International Transactions on Power Engineering
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    • v.5A no.4
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    • pp.357-365
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    • 2005
  • This research investigates the influences of distributed generations (DG), which are interconnected to the bus by the dedicated lines, on the overcurrent relays (OCR) of the neighboring distribution feeders and also proposes a novel method to reduce the negative effects on the feeder protection. Due to the grid connected DG, the entire short-circuit capacity of the distribution networks increases, which may raise the current of the distribution feeder during normal operations as well as fault conditions. In particular, during the switching period for loop operation, the current level of the distribution feeder can be larger than the pickup value for the fault of the feeder's OCR, thereby causing the OCR to perform a mal-operation. This paper proposes the adaptive setting algorithm for the OCR of the distribution feeders having the neighboring dedicated feeders for the DG to prevent the mal-operations of the OCR under normal conditions. The proposed method changes the pickup value of the OCR by adapting the power output of the DG monitored at the relaying point in the distribution network. We tested the proposed method with the actual distribution network model of the Hoenggye substation at the Korea Electric Power Co., which is composed of five feeders supplying the power to network loads and two dedicated feeders for the wind turbine generators. The simulation results demonstrate that the proposed adaptive protection method could enhance the conventional OCR of the distribution feeders with the neighboring dedicated lines for the DG.

An Efficient Management Strategy of A Offline Second-Hand Bookstore With Camera Type OCR Technology (카메라형 광학식문자판독기술(OCR)을 활용한 오프라인 중고서점의 장서 디지털 데이터화 관리 방안 제안)

  • Koo, Ja Min;Ham, Seung Mo;Kim, Woo Je;Shim, Hyun Dong;Ryu, Ki Don
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2014.01a
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    • pp.283-286
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    • 2014
  • 본 논문에서는 카메라형 OCR (Optical Character Reader) 기술을 이용해 오프라인 중고서점의 효율적 장서관리 시스템을 구축하기 위한 디지털 데이터화 관리시스템 방안을 제안한다. OCR은 광학적으로 인식할 수 있는 문자를 컴퓨터가 읽을 수 있도록 하는 기술이다. 원리적으로 문자 한 개를 수십 개의 모눈으로 분할해 특정한 모눈의 흑백 또는 자획형상 특징에 의해 문자를 판독한다. 이 논문에서는 OCR 기술을 활용함으로써 디지털 데이터화의 효과는 물론 적용 환경의 개선효과를 기대해 볼 수 있는 오프라인 중고서점 시장을 목표로 했다. 오프라인 중고서점에서 보유하고 있는 장서의 디지털 데이터화는 기업형 중고서점과의 경쟁에 있어서도 생존을 위해 필요한 요소이다. 카메라형 OCR 기술을 활용한 장서 디지털 데이터화는 오프라인 중고서점 판매자가 도서재고 검색 및 판매 관리 효율을 높이도록 도와줄 뿐 아니라, 도서판매 유형, 소비자 분석과 수요 예측을 가능하게 한다. 또한 소비자에게 오프라인 중고서점에서 보유하고 있는 희귀 장서와 중고서적들을 검색해 구입할 수 있는 편의를 제공할 것이다. 오프라인 중고서점 판매를 촉진하고 활성화시킨다면 출판의 선순환적 구조를 만드는 데 기여할 것으로 예상된다.

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Deep Learning OCR based document processing platform and its application in financial domain (금융 특화 딥러닝 광학문자인식 기반 문서 처리 플랫폼 구축 및 금융권 내 활용)

  • Dongyoung Kim;Doohyung Kim;Myungsung Kwak;Hyunsoo Son;Dongwon Sohn;Mingi Lim;Yeji Shin;Hyeonjung Lee;Chandong Park;Mihyang Kim;Dongwon Choi
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.143-174
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    • 2023
  • With the development of deep learning technologies, Artificial Intelligence powered Optical Character Recognition (AI-OCR) has evolved to read multiple languages from various forms of images accurately. For the financial industry, where a large number of diverse documents are processed through manpower, the potential for using AI-OCR is great. In this study, we present a configuration and a design of an AI-OCR modality for use in the financial industry and discuss the platform construction with application cases. Since the use of financial domain data is prohibited under the Personal Information Protection Act, we developed a deep learning-based data generation approach and used it to train the AI-OCR models. The AI-OCR models are trained for image preprocessing, text recognition, and language processing and are configured as a microservice architected platform to process a broad variety of documents. We have demonstrated the AI-OCR platform by applying it to financial domain tasks of document sorting, document verification, and typing assistance The demonstrations confirm the increasing work efficiency and conveniences.

The Modeling of OverCurrent Relay using Dynamic Link Library (Dynamic Link Library 기법을 이용한 과전류 계전기 모델링)

  • Seong, No-Kyu;Seo, Hun-Chul;Yeo, Sang-Min;Kim, Chul-Hwan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.6
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    • pp.1065-1070
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    • 2009
  • This paper presents the new technique of modeling using Dynamic Link Library(DLL) in ElectroMagnetic Transients Program - Restructured Version(EMTP-RV) in which we have simplified the procedures of OverCurrent Relay(OCR) modeling. The DLL function is designed to allow EMTP-RV users to develop advanced program model modules and interface them directly and intimately with the EMTP-RV engine. The modeled OCR is verified by simulating the various fault cases in the distribution system. Also, the performance for the modeling of OCR using DLL is compared with that of the method using the control components of EMTP-RV and using EMTP/MODELS. The results show the validity of modeled OCR and the effectiveness of the method using DLL function.