• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.73-79
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• 2021

In the wave of the 4th industrial revolution, smart factory is required in many factories. However, small and mid-sized companies (SMEs) still have aging machines and are having difficulties in the data collection stage, which is the basis of smart factories. This study proposes a low cost monitoring method by using an open source based technology that extracts data from the image of the facility control panel without the need for modification of existing facilities. The proposed method was tested and evaluated for forging facilities in automobile parts manufacturing plants through prototyping. As a result of the evaluation, it was confirmed that low-cost facility monitoring is possible, and it will help SMEs build smart factories.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.193-195
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• 2002

In this paper, a communication module is proposed to be applied to communication between over current relay (OCR) agents in multi agent protection system. A multi agent system can achieve a global goal beyond the ability of each individual agent by working together, in which it is the prerequisite for each agent to be able to exchange or share information or processing status with other agent. The proposed communication module is purposed to enable not only each agent to bring about its own goal, but also the whole protective system to provide much improved coordinated protection. It is applied to a self adaptive protection system for a distribution network using multi agent concept to show its effectiveness.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.117-140
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• 2013

Hindi is the most widely spoken language in India, with more than 300 million speakers. As there is no separation between the characters of texts written in Hindi as there is in English, the Optical Character Recognition (OCR) systems developed for the Hindi language carry a very poor recognition rate. In this paper we propose an OCR for printed Hindi text in Devanagari script, using Artificial Neural Network (ANN), which improves its efficiency. One of the major reasons for the poor recognition rate is error in character segmentation. The presence of touching characters in the scanned documents further complicates the segmentation process, creating a major problem when designing an effective character segmentation technique. Preprocessing, character segmentation, feature extraction, and finally, classification and recognition are the major steps which are followed by a general OCR. The preprocessing tasks considered in the paper are conversion of gray scaled images to binary images, image rectification, and segmentation of the document's textual contents into paragraphs, lines, words, and then at the level of basic symbols. The basic symbols, obtained as the fundamental unit from the segmentation process, are recognized by the neural classifier. In this work, three feature extraction techniques-: histogram of projection based on mean distance, histogram of projection based on pixel value, and vertical zero crossing, have been used to improve the rate of recognition. These feature extraction techniques are powerful enough to extract features of even distorted characters/symbols. For development of the neural classifier, a back-propagation neural network with two hidden layers is used. The classifier is trained and tested for printed Hindi texts. A performance of approximately 90% correct recognition rate is achieved.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.31-38
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• 2024

In this paper, we propose an ASAP(AI-driven Service for Advertisement Production) application that provides a generative AI-based automatic advertising image production service. This application utilizes GPT-3.5 Turbo Instruct to generate suitable background mood and promotional copy based on user-entered keywords. It utilizes OpenAI's DALL·E 3 model and Stability AI's SDXL model to generate background images and text images based on these inputs. Furthermore, OCR technology is employed to improve the accuracy of text images, and all generated outputs are synthesized to create the final advertisement. Additionally, using the PILLOW and OpenCV libraries, text boxes are implemented to insert details such as phone numbers and business hours at the edges of promotional materials. This application offers small business owners who face difficulties in advertising production a simple and cost-effective solution.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.111-115
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• 2017

Terahertz waves are superior to conventional X-ray or Magnetic Resonance Tomography(MRI), and the amount of information that can be transmitted is as large as thousands of times that conventional X-ray or MRI. In addition, Terahertz waves have great performance in analyzing an object which have some layered structure. By using this advantage, we can extract the letters of a page by analyzing information such as absorption amount and reflection amount by irradiating a closed book with pulses of various frequencies within gap of a terahertz wave. However, in the image of each page using the Terahertz wave might be obtained various kinds of noise and the different character occlusion region. So, to extract letters from the terahertz image, we must take the noise and occlusion region away. We have been working to enhancement the image quality in various ways, and keep on studying de-noising processing for enhancement about the image quality and high resolution. Finally, we also keep on studying about OCR(Optical Character Recognition) technology, which based on pattern matching technique, to read letters.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.02a
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• pp.59-70
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• 2000

본 연구에서는 콘관입속도가 콘관입시험 결과에 미치는 영향을 연구하기 위하여 LSU/CALCHAS(Louisiana State University Calibration Chamber System)를 이용한 미니 Piezocone의 관입시험이 수행되었으며 그 결과를 비교 분석하였다. 10회의 미니 Piezocone 관입시험이 Ko 조건에서 수행되었으며 33% kaolin, 67% sand mixture가 시료로 사용되었고, 콘관입속도 0.3, 0.6cm/sec, U1(filter element at the cone tip), U2(filter element above the cone base), OCR=1, 10 의 조건이 다양하게 적용되었다. 시험결과 Cone Resistance, Excess Pore Water Pressure, Sleeve Friction 은 U1, U2 두 종류의 콘에 대해서 모두 관입속도가 커짐에 따라 증가하였으나 OCR의 증가에 따라서는 감소하였으며 U1의 Excess Pore Water Pressure가 U2 경우보다 크게 측정되었다.

• The Journal of Bigdata
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• v.5 no.1
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• pp.29-39
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• 2020

Purpose The atmosphere of respect for individual tastes that have spread throughout society has changed the consumption trend. As a result, the travel industry is also seeing customized travel as a new trend that reflects consumers' personal tastes. In particular, there is a growing interest in 'film-induced tourism', one of the areas of travel industry. We hope to satisfy the individual's motivation for traveling while watching movies with customized travel proposals, which we expect to be a catalyst for the continued development of the 'film-induced tourism industry'. Design/methodology/approach In this study, we implemented a methodology through 'OCR' of extracting and suggesting film location information that viewers want to visit. First, we extract a scene from a movie selected by a user by using 'OpenCV', a real-time image processing library. In addition, we detected the location of characters in the scene image by using 'EAST model', a deep learning-based text area detection model. The detected images are preprocessed by using 'OpenCV built-in function' to increase recognition accuracy. Finally, after converting characters in images into recognizable text using 'Tesseract', an optical character recognition engine, the 'Google Map API' returns actual location information. Significance This research is significant in that it provides personalized tourism content using fourth industrial technology, in addition to existing film tourism. This could be used in the development of film-induced tourism packages with travel agencies in the future. It also implies the possibility of being used for inflow from abroad as well as to abroad.

• Journal of Electrical Engineering and Technology
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• v.1 no.2
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• pp.137-144
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• 2006

This paper proposes novel protection schemes for grid-connected distributed generation (DG) units using the fault location algorithm. The grid-connected DG would be influenced by abnormal distribution line conditions. Identification of the fault location for the distribution lines at the relaying point of DG helps solve the problems of the protection relays for DG. The proposed scheme first identifies fault locations using currents and voltages measured at DG and source impedance of distribution networks. Then the actual faulted feeder is identified, applying time-current characteristic curves (TCC) of overcurrent relay (OCR). The method considering the fault location and TCC of OCR might improve the performance of the conventional relays for DG. Test results show that the method prevents the superfluous operations of protection devices by discriminating the faulted feeder, whether it is a distribution line where DG is integrated or out of the line emanated from the substation to which the DGs are connected.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.495-496
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• 2007

An Over Current Relayng algorithm using 80c196kc micro processor was realized in this paper. This OCR Algorithm was verified with simulated fault signal. The fault signal was made by EMTP and realized by DOBLE to compare H/W test with S/W test. This simulations showed similar result between H/W and S/W test.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.967-973
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• 2020

As the implementation of export controls is spreading, the importance of classifying strategic items is increasing, but Korean export companies that are new to export controls are not able to understand the concept of strategic items, and it is difficult to classifying strategic items due to various criteria for controlling strategic items. In this paper, we propose a method that can easily approach the process of classification by lowering the barrier to entry for users who are new to export controls or users who are using classification of strategic items. If the user can confirm the decision result by providing a manual or a catalog for the procedure of classifying strategic items, it will be more convenient and easy to approach the method and procedure for classfying strategic items. In order to achieve the purpose of this study, it utilizes deep learning, which are being studied in image recognition and classification, and OCR(optical character reader) technology. And through the research and development of the support tool, we provide information that is helpful for the classification of strategic items to our companies.