• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2563-2573
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• 1999

In most mail automatic processing centers, after facing and canceling, letter mails are passed through an Optical Character Recognition/Barcode Sorter(OCR/BS) to read the postal code and 3 of 5 fluorescent (luminescent) barcode is applied. Normally, 31%∼35% of this mails are rejected. The main reasons for reading failures are poor printing quality of addresses and barcodes, script printing, writing in a cursive hand, variety fonts, and failure to locate the address. Our goal is to provide mailer with top quality service and customer barcode service as we move toward 100% barcoding automation of letter mail. In this paper, we propose a method of printing 3 of 5 customer barcode, postal code management, and detection of postal code based on postal address for increase the performance of automatic processing system in mail items. Using postal code generating rules, which are automatically extracted from postal addresses and address numbers, creates postal codes. The customer barcode support system is implemented by C++ language and runs on IBM PC under Windows 95.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1342-1349
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• 1999

본 논문에서는 문서 내의 인접한 두 행 사이에는 일정한 두께의 공백 행이 존재하며 그 공백 행의 기울기는 실제 문서의 기울어진 정도를 반영한다는 사실에 기반하여, 선형적으로 기울어진 문서 영상의 기울기 추정을 위한 고속의 알고리즘을 제안한다. 먼저, 간단한 모폴로지 연산(dilation)을 이용하여 문자행 영역과 공백행 영역을 분리한 후, 이를 일정 간격으로 수직 샘플링하여 수직선 상에 있는 모든 공백행의 중심점(행간점)을 찾는다. 동일한 공백 행 상에 있는 인접한 두 행간점 간에 기울기를 계산하고, 전체 영상으로부터 이들의 분포를 조사하여 최대 빈도를 가지는 기울기를 입력 문서의 기울기로 추정한다. 실험에서는 제안한 알고리즘을 필기체 및 인쇄체를 포함하는 다양한 형태의 가로쓰기 문서에 적용한 결과를 보인다.Abstract In this paper, we propose a fast algorithm to estimate the skew angle of linearly skewed document images. This paper is based on the fact that there is a blank line with uniform thickness between two adjacent text lines and the slope of the line is the same as that of the document. Firstly, we apply a dilation operation to the image to separate blank lines from text lines, and we detect center points of blank lines along the vertically sampled lines. Then we calculate the slope between neighboring center points in the same blank line. Calculated slopes for the entire image are accumulated on the histogram to display the distribution of them. Finally, the peak in the histogram is detected and estimated as the slope of the document image. In the experiments, we adopted a lot of images of various format with hand-printed or machine-printed document to verify our algorithm.

• Journal of Sericultural and Entomological Science
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• v.45 no.2
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• pp.80-84
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• 2003

The component and content of free sugar in mulberry fruits were evaluated. In all accessions, fructose and glucose were identified as the major free sugar. The ratio of two components appeared in the same level. But CV (coefficient of variation. ％) of fructose and glucose were 23.6％, 23.4％, respectively. It might suggest that varietal variation exists in sugar contents. The mean of total free sugars were 9.11${\pm}$2.14％. Among the tested 49 accessions, ‘Geunanosang’ showed the highest total free sugars in 14.67％, whereas ‘Cheongsipyung’ showed the lowest total free sugars in 5.57％. Also fruity characteristics as well as total free sugars to select the desirable mulberry varieties for the production of fruit were researched and analyzed. From that results, four suitable varieties such as ‘Hwansipchosaeng’, ‘Junggojo’, ‘ Kaery-angchosaengsipmunja’, and ‘Geunanosang’ were selected.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.774-784
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• 2021

The object detection and recognition process is a very important task in the field of computer vision, and related research is actively being conducted. However, in the actual object recognition process, the recognition accuracy is often degraded due to the resolution mismatch between the training image data and the test image data. To solve this problem, in this paper, we designed and developed an integrated object recognition and super-resolution framework by proposing an image super-resolution technique to improve object recognition accuracy. In detail, 11,231 license plate training images were built by ourselves through web-crawling and artificial-data-generation, and the image super-resolution artificial neural network was trained by defining an objective function to be robust to the image flip. To verify the performance of the proposed algorithm, we experimented with the trained image super-resolution and recognition on 1,999 test images, and it was confirmed that the proposed super-resolution technique has the effect of improving the accuracy of character recognition.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.989-998
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• 2023

As diseases are already increasing due to aging population and changes in eating habits, interest in digital healthcare is increasing. According to the 2020 Elderly Status Survey, 84% of South Koreans aged 65 and older suffer from at least one chronic disease, and the number and duration of drugs taken by the elderly are also increasing. Effective management that enhances compliance of chronic disease patients can prevent the onset of complications, thereby averting progression to severe illnesses. Thus, a proper medication-taking habit is crucial. This paper proposes a medication information retrieval system using OCR technology. By leveraging Google Cloud Vision API, the system detects and recognizes the names of medicines. Once recognized, the medication name is searched in a database to provide users with medication information and medication schedule management services. By providing accurate medication information through the search, it is possible to induce changes in medication methods and habits. By eliminating the inconvenience of direct input through OCR technology, we anticipate enhancing user convenience by promptly delivering information.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.3
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• pp.13-22
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• 2024

Currently, with the proliferation of digital devices, the significance of handwritten texts in daily lives is gradually diminishing. As the use of keyboards and touch screens increase, a decline in Korean handwriting quality is being observed across a broad spectrum of Korean documents, from young students to adults. However, Korean handwriting still remains necessary for many documentations, as it retains individual unique features while ensuring readability. To this end, this paper aims to implement an application designed to improve and correct the quality of handwritten Korean script The implemented application utilizes the CRAFT (Character-Region Awareness For Text Detection) model for handwriting area detection and employs the VGG-Feature-Extraction as a deep learning model for learning features of the handwritten script. Simultaneously, the application presents the user's handwritten Korean script's reliability on a syllable-by-syllable basis as a recognition rate and also suggests the most similar fonts among candidate fonts. Furthermore, through various experiments, it can be confirmed that the proposed application provides an excellent recognition rate comparable to conventional commercial character recognition OCR systems.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.1-15
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• 2006

In Korea, a resident registration card has various personal information such as a present address, a resident registration number, a face picture and a fingerprint. A plastic-type resident card currently used is easy to forge or alter and tricks of forgery grow to be high-degree as time goes on. So, whether a resident card is forged or not is difficult to judge by only an examination with the naked eye. This paper proposed an automatic recognition method of a resident card which recognizes a resident registration number by using a refined ART2-based RBF network newly proposed and authenticates a face picture by a template image matching method. The proposed method, first, extracts areas including a resident registration number and the date of issue from a resident card image by applying Sobel masking, median filtering and horizontal smearing operations to the image in turn. To improve the extraction of individual codes from extracted areas, the original image is binarized by using a high-frequency passing filter and CDM masking is applied to the binaried image fur making image information of individual codes better. Lastly, individual codes, which are targets of recognition, are extracted by applying 4-directional contour tracking algorithm to extracted areas in the binarized image. And this paper proposed a refined ART2-based RBF network to recognize individual codes, which applies ART2 as the loaming structure of the middle layer and dynamicaly adjusts a teaming rate in the teaming of the middle and the output layers by using a fuzzy control method to improve the performance of teaming. Also, for the precise judgement of forgey of a resident card, the proposed method supports a face authentication by using a face template database and a template image matching method. For performance evaluation of the proposed method, this paper maked metamorphoses of an original image of resident card such as a forgey of face picture, an addition of noise, variations of contrast variations of intensity and image blurring, and applied these images with original images to experiments. The results of experiment showed that the proposed method is excellent in the recognition of individual codes and the face authentication fur the automatic recognition of a resident card.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.6
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• pp.47-55
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• 2003

In this paper, we propose a new approach to detect peculiar features of license plates using intensity vector and composite color component in order to extract license plates from parking regulation images, which is captured in various locations around the front or the rear of cars at various times and places, and in which complex background is included. We fundamentally use both features that intensity value repeats frequently increasing and decreasing because intensity is obviously different at numerics and background, and that color is uniform in the area of license plates. First, we search each row at regular intervals starting from the bottom of a license-plate image, and we set up a rough region for a certain zone in which tile sign of intensity vector changes frequently enough and color of license plate is detected enough, assuming it as a candidate location of a license plate. And then, we extract an elaborate area of a license plate by projecting vertical edges horizontally and vertically. Here, type of cars, such as the urinate and the public, is easily classified according to the color of extracted plates. We used 200 actual regulation images, which are captured at various times and places, to evaluate the performance of the proposed method. As a result, the proposed method showed extraction rate of 96%, which is 9% higher than the previous method using only intensity vector.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.7 no.1
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• pp.25-31
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• 2009

An analytical method of $^{99}Tc$ concentration in soil was set up and discussed considering the $^{99}Tc$ concentration in Korean soil measured with its analytical method. A selective TEVA resin was used to separate and purify the $^{99}Tc$ in the soil sample. $^{99m}Tc$ from a commercial $^{99}Mo/^{99m}Tc$ generator was used as a yield tracer for the chemical separation of $^{99}Tc$ and its problem when using $^{99m}Tc$ as a tracer was discussed. The chemical recovery yield of $^{99}Tc$ was above 70%. The optimum conditions of inductively coupled plasma mass spectrometry system(ICP-MS) were set up to determine the $^{99}Tc$ after the separation process. The minimum detectable activity(MDA) was 15 mBq/kg-dry in this analytical procedure. The $^{99}Tc$ concentration in soils of Jeju and Kori were measured in the rage of 33.73-89.16 mBq/kg-dry. Those values were less than those reported in other countries and seemed to be originated from atmospheric fallout.

• Analytical Science and Technology
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• v.29 no.2
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• pp.65-72
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• 2016

This study presented an analytical method for detecting radium in soils using a liquid scintillation counter (LSC). The isotope ²²⁶Ra was extracted from soil using the fusion method and then separated from interfering radionuclides using the precipitation method. Radium was coprecipitated as sulfate salts with barium (Ba) and then converted into Ba(Ra)CO₃, which is soluble in an acidic solution. The isotope ²²²Rn, the decay progeny of ²²⁶Ra, was trapped in a water immiscible cocktail and analyzed by LSC. The pulse shape analysis (PSA) level was estimated using ⁹⁰Sr and ²²⁶Ra standard solutions. The figure of merit was the highest at PSA 80, while the alpha spillover was the lowest at PSA 80. The counting efficiency was 243 ± 2% in a glass vial. This analytical method was verified with International Atomic Energy Agency (IAEA) reference materials, including IAEA-312, IAEA-314, and IAEA-315. The recovery ranged from 60–82%, while the relative bias between the measured value and the recommended value was less than 10%. The minimum detectable activity was 2.1 Bq kg⁻¹ with dry mass 1 g, the background count rate of 0.02 cpm, the recovery rate of 70% and counting time of 30 min.