• Proceedings of the Korean Information Science Society Conference
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• 2002.10c
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• pp.472-474
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• 2002

공개키 기반 구조에서 가장 비용이 많이 드는 부분이 인증서가 유효한지 여부를 검증하는 것이다. 특히 고액의 주식 거래나 전자상거래에서 실시간 인증서 상태 검증은 반드시 필요하다. 그동안 연구되어 왔던 인증서 폐지 여부를 확인하는 방법으로 CRL, delta-CRL, OCSP, CRTs, CRSL 등의 방법들이 제안되었다. 하지만, 이들 방법들은 즉시성과 네트워크 비용간의 trade-off가 발생하는 문제점이 있다. 본 논문에서는 Simple skip lists를 사용하여 인증서 사용 용도에 따라 알맞게 서비스를 제공하는 방안인 OCRS를 제안한다.

• 프린팅코리아
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• s.58
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• pp.156-157
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• 2007

• The monthly packaging world
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• s.252
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• pp.56-61
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• 2014

• 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.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.7
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• pp.930-935
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• 2004

The present study was aimed to study the effect of aqueous extract of Tinospora cordifolia and autologous plasma on uterine infections. Buffaloes in estrus, 40 days and above postpartum were checked for uterine infections. Animals having uterine infections were randomly divided into three groups of six animals each. Buffaloes in group I, II and III (control) were given intrauterine infusion of aqueous extract of Tinospora cordifolia (3,000 mg total dose), autologous plasma (150 ml) and phosphate buffer saline (150 ml) respectively, in three divided doses, once daily for three consecutive days, starting from the day of estrus. A fourth group (IV) comprising of six buffaloes having no uterine infection was also included in the present study. Buffaloes were inseminated artificially on next estrus following treatment and confirmed for pregnancy 60 days later. Bacterial population in CVM of buffaloes in group I, II and III was significantly (p<0.05) higher than group IV. After treatment there was a significant (p<0.01) reduction in bacterial population in group I (83.496$\pm$7.755%) and group II 80.233$\pm$5.799%) than group in III 7.557$\pm$33.551%) at next estrus. There was non-significant improvement in first service conception rate (CR, 33.33%) and overall conception rate (OCR, 27.27%) in group I, in comparison to group III (first service CR-16.67%; OCR-20.0%). No significant improvement was seen in OCR (22.22%) in-group II also in comparison to group III. The improvement in group I was however, nonsignificantly lower than normal animals of group IV (First service CR-16.67%; OCR-36.33%).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.318-328
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• 2014

In this paper, as a way of performance improvement of business card recognition in the mobile environment, we suggested a hybrid OCR agent which combines data using a parallel processing sequence between various algorithms and different kinds of business card recognition engines which have learning data. We also suggested an Image Processing Method on mobile cameras which adapts to the changes of the lighting, exposing axis and the backgrounds of the cards which occur depending on the photographic conditions. In case a hybrid OCR agent is composed by the method suggested above, the average recognition rate of Korean business cards has improved from 90.69% to 95.5% compared to the cases where a single engine is used. By using the Image Processing Method, the image capacity has decreased to the average of 50%, and the recognition has improved from 83% to 92.48% showing 9.4% improvement.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.5
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• pp.29-41
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• 2022

Alien species cause problems in various ecosystems, reduce biodiversity, and destroy ecosystems. Due to these problems, the problem of a management plan is increasing, and it is difficult to accurately identify each individual and calculate the number of individuals, especially when researching alien turtle species such as GPS and PIT based on capture. this study intends to conduct an individual recognition study using a UAV. Recently, UAVs can take various sensor-based photos and easily obtain high-definition image data at low altitudes. Therefore, based on previous studies, this study investigated five variables to be considered in UAV flights and produced a test paper using them. OCR was used to monitor the displayed turtles using the manufactured test paper, and this confirmed the recognition rate. As a result, the use of yellow numbers showed the highest recognition rate. In addition, the minimum threat distance was confirmed to be 3 to 6m, and turtles with a shell size of 6 to 8cm were also identified during the flight. Therefore, we tried to propose an object recognition methodology for turtle display text using OCR, and it is expected to be used as a new turtle monitoring technique.

• Journal of Ocean Engineering and Technology
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• v.15 no.4
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• pp.92-100
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• 2001

It is very important to determine the coefficient of earth pressure at rest accurately in order to estimate the behavior of soil structure. For estimation of K/sub 0/-value depending upon the stress history of dry sand, a new type of K/sub 0/-oedeometer apparatus is devised, and the horizontal earth pressure is accurately measured. For this study, 2 types of one-cyclic K/sub 0/-Loading/unloading models have been studied experimentally using four relative densities of the sand. The results obtained in this test are as follows : K/sub on'/ the coefficient of earth pressure at - rest for virgin loading is a function of the angle of internal friction Φ' of the sand and is determined as K/sub on/=1 - 0.914 sin Φ', K/sub ou'/ the coefficient of earth pressure at rest for virgin unloading is a function of K/sub on/ and over consolidation ratio(OCR), and is determined as K/sub ou/=K/sub on/(OCR)K/sup a/. The exponent α, increases as the relative density increases. K/sub or'/ the coefficient of earth pressure at rest for virgin reloading decreases in hyperbola type as the vertical stress, σ/sub v/’, increases. And, the stress path at virgin reloading leads to the maximum prestress point, independent upon the value of the minimum unloading stress. The gradient of this curve, m/sub r/ increases as OCR increases.

• ETRI Journal
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• v.32 no.5
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• pp.729-739
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• 2010

Due to the rapid development of mobile devices equipped with cameras, instant translation of any text seen in any context is possible. Mobile devices can serve as a translation tool by recognizing the texts presented in the captured scenes. Images captured by cameras will embed more external or unwanted effects which need not to be considered in traditional optical character recognition (OCR). In this paper, we segment a text image captured by mobile devices into individual single characters to facilitate OCR kernel processing. Before proceeding with character segmentation, text detection and text line construction need to be performed in advance. A novel character segmentation method which integrates touched character filters is employed on text images captured by cameras. In addition, periphery features are extracted from the segmented images of touched characters and fed as inputs to support vector machines to calculate the confident values. In our experiment, the accuracy rate of the proposed character segmentation system is 94.90%, which demonstrates the effectiveness of the proposed method.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06c
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• pp.412-416
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• 2007

본 논문에서는 OCR(Optical Character Recognition)의 정확도를 위해 인쇄체 한글 문서 영상에 대한 자동 평가방법을 제안한다. 자동 평가방법은 문서가 스캔된 상태에 따라 낮은 해상도, 영상 자체의 기울어짐, 많은 잡음 등을 판단하여 인식하지 않고도 인식률을 추측할 수 있다. 평가방법은 영상 자체의 밝기, 기울기, 영역의 특징, 문자의 상태 등을 특징 항목으로 만들어 점수를 산출한다. 각 항목의 점수는 가장 높은 인식률을 가지는 영상의 특징 값을 기준으로 삼는다. 각각의 특징에 대해 점수가 산출되면 인식률에 높은 비중을 차지하는 특징에 높은 가중치를 적용하여 최종 점수를 산출한다. 영상 평가방법을 통해 높은 점수를 얻은 영상은 상용 인식기를 통해 인식한 결과 높은 인식률을 나타냈고, 평가방법에서 낮은 점수를 받은 영상은 상대적으로 낮은 인식률을 나타냈다. 본 논문에서 제안하는 문서영상을 위한 자동 평가방법은 인식기를 사용하지 않고 영상의 품질을 측정하기 때문에 빠른 시간에 인식률을 추측할 수 있고, 낮은 인식률을 보일 수 있는 영상에 대해서는 항목별 점수를 피드백으로 사용할 수 있어 인식하기전 문서 영상의 전처리에 과정에 도움을 줄 수 있다.