• Title/Summary/Keyword: automatic processing

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The Hangul 4 State Bar Code System for the Automatic processing of Mail Items (우편물 자동처리를 위한 한글 4 State 바코드 시스템)

  • Park, Moon-Sung;Song, Jae-Gwan;Woo, Dong-Chin
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.1
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    • pp.146-155
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    • 2000
  • This paper describes a 4-state bar code called HANGUL 4 ST that has been specifically designed for automatic processing of the letter mails, A HANGUL 4 ST bar code is a necessary data base that is applied data capture and data carrier with it all the information necessary for sorting, the amount capture for transportation of mail items, and valued-added services such as indicia, tracking and trace. The 4-state bar code information contents are composed of a postal code, delivery point, customer information including customer identification number and name, and parity bits for error detect and correct. The data density capability of HANGUL 4 St allows all useful sorting data and customer data to be encoded on one label. This supports better automatic processing in mail items, higher level of customer service and more efficient operation.

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Development of Automatic Nut Inspection System using Image Processing (이미지 프로세싱을 이용한 자동 너트 검사 장비 개발)

  • Lee, Sang-Hak;Seo, Myong-Ho;Chung, Tae-Choong
    • The KIPS Transactions:PartA
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    • v.11A no.4
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    • pp.235-242
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    • 2004
  • When manufacturing information and communication device that consists of lots of part, it is important to improve the quality of the produced system by inspecting the system accurately and exclude the defected part. In case of LCD which is recently in a great demand, the inspection process of the nut which bonds the back frame to protect the LCD panel has to be done by human labor. It highly required an automatic inspection system which can inspect the nut without wasting human resources. In this paper, we describe the process of developing a system which automatically inspect the status of nuts inserted during the manufacturing of LCD. The nut inspection vision system developed measures the number of nut's spiral, the distance between pitches, the width of a pitch, and the inside diameter of nut. We have adopted lens with high magnifying power and calibration tool and intended to produce automatic lighting for maintaining a stable environment for a high precision system. We also developed the algorithms for analyzing the nut. We apply the system to real factory field and verify that it is better than the man power in terms of error rate.

A Study on Automatic Detection of Uterine' Cervical Pap- Smears by Image Processing (영상처리를 이용한 자궁경부 세포진의 자동탐색 방법에 관한 연구)

  • Un, Sung-Kyung;Park, Chan-Mo;Park, Hwa-Choon;Yoon, So-Young;Cho, Min-Sun;Cho, Soo-Yeon;Kim, Sung-Sook
    • The Korean Journal of Cytopathology
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    • v.5 no.1
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    • pp.15-22
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    • 1994
  • Cancer of the cervix is the most common malignancy in women in developing countries and the second most common cancer in women throughout the world with approximately 500,000 new cases each year. Prevention of this large number of premature deaths among women is, therefore, a goal worthy of urgent and serious consideration. Due to its high diagnostic disagreement among pathologists and large quantity of specimens, it is necessary to develop an automatic screening system measuring morphologic and densitometric features of the samples. Many research works have been published but most of them used Feulgen stained specimens which are not a usual staining method used in clinics. In this thesis, an automatic cancerous nucleus detection method essential to a screening system with papanicolaou stained specimens called Pap-smear is proposed which employs image processing techniques. It uses edge information to segment objects and morphologic as well as densitometric information to distinguish cancerous nuclei from dirts or normal nuclei. It has produced useful results in our study.

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Automatic Recognition of the Front/Back Sides and Stalk States for Mushrooms(Lentinus Edodes L.) (버섯 전후면과 꼭지부 상태의 자동 인식)

  • Hwang, H.;Lee, C.H.
    • Journal of Biosystems Engineering
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    • v.19 no.2
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    • pp.124-137
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    • 1994
  • Visual features of a mushroom(Lentinus Edodes, L.) are critical in grading and sorting as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. To realize the automatic handling and grading of mushrooms in real time, the computer vision system should be utilized and the efficient and robust processing of the camera captured visual information be provided. Since visual features of a mushroom are distributed over the front and back sides, recognizing sides and states of the stalk including the stalk orientation from the captured image is a prime process in the automatic task processing. In this paper, the efficient and robust recognition process identifying the front and back side and the state of the stalk was developed and its performance was compared with other recognition trials. First, recognition was tried based on the rule set up with some experimental heuristics using the quantitative features such as geometry and texture extracted from the segmented mushroom image. And the neural net based learning recognition was done without extracting quantitative features. For network inputs the segmented binary image obtained from the combined type automatic thresholding was tested first. And then the gray valued raw camera image was directly utilized. The state of the stalk seriously affects the measured size of the mushroom cap. When its effect is serious, the stalk should be excluded in mushroom cap sizing. In this paper, the stalk removal process followed by the boundary regeneration of the cap image was also presented. The neural net based gray valued raw image processing showed the successful results for our recognition task. The developed technology through this research may open the new way of the quality inspection and sorting especially for the agricultural products whose visual features are fuzzy and not uniquely defined.

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Implementation of OMR Answer Paper Scoring Method Using Image Processing Method (영상처리기법을 활용한 OMR 답안지 채점방법의 구현)

  • Kwon, Hiok-Han;Hwang, Gi-Hyun
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.3
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    • pp.169-175
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    • 2011
  • In this paper, an automatic scoring system of the OMR answer sheet is implemented using Gray Scale and image segmentation method. The proposed method was used to extract the OMR data on multiple-choice answer sheet from captured image. In addition, On-line scoring system is developed and implemented to mark the short-answer type on the reverse side. Therefore, teachers can mark the short-answer type for anytime and anywhere within the available time. There were many advantages to mark of the multiple-choice answer sheet without additional OMR reader. In the future, the grading of short-answer type will be more efficient if it were performed by using an automatic scoring system based on image processing.

Development of an Automatic Sweet Potato Sorting System Using Image Processing (영상처리를 이용한 고구마 자동 선별시스템 개발)

  • Yang G. M.;Choi K. H.;Cho N. H.;Park J. R.
    • Journal of Biosystems Engineering
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    • v.30 no.3 s.110
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    • pp.172-178
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    • 2005
  • Grading and sorting an indeterminate form of agricultural products such as sweet potatoes and potatoes are a labor intensive job because its shape and size are various and complicate. It costs a great deal to sort sweet potato in an indeterminate forms. There is a great need for an automatic grader fur the potatoes. Machine vision is the promising solution for this purpose. The optical indices for qualifying weight and appearance quality such as shape, color, defects, etc. were obtained and an on-line sorting system was developed. The results are summarized as follows. Sorting system combined with an on-line inspection device was composed of 5 sections, human inspection, feeding, illumination chamber, image processing & control, and grading & discharging. The algorithms to compute geometrical parameters related to the external guality were developed and implemented for sorting the deformed sweet potatoes. Grading accuracy by image processing was $96.4\%$ and the processing capacity was 10,800 pieces per hour.

Training Method of Artificial Neural Networks for Implementation of Automatic Composition Systems (자동작곡시스템 구현을 위한 인공신경망의 학습방법)

  • Cho, Jae-Min;Ryu, Eun Mi;Oh, Jin-Woo;Jung, Sung Hoon
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.8
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    • pp.315-320
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    • 2014
  • Composition is a creative activity of a composer in order to express his or her emotion into melody based on their experience. However, it is very hard to implement an automatic composition program whose composition process is the same as the composer. On the basis that the creative activity is possible from the imitation we propose a method to implement an automatic composition system using the learning capability of ANN(Artificial Neural Networks). First, we devise a method to convert a melody into time series that ANN can train and then another method to learn the repeated melody with melody bar for correct training of ANN. After training of the time series to ANN, we feed a new time series into the ANN, then the ANN produces a full new time series which is converted a new melody. But post processing is necessary because the produced melody does not fit to the tempo and harmony of music theory. In this paper, we applied a tempo post processing using tempo post processing program, but the harmony post processing is done by human because it is difficult to implement. We will realize the harmony post processing program as a further work.

Automatic Testing Based on a Simulink (Simulink 기반의 Test 환경)

  • Kim Jae Youl
    • Proceedings of the Korea Information Processing Society Conference
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    • 2008.11a
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    • pp.543-545
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    • 2008
  • 시스템은 자발성, 자율성, 사회성, 반응성을 갖는 독립된 프로그램인 에이전트를 조합하여 구성되는 시스템으로, 일반 사용자에게 편리하고 자연스러운 메타포를 제공한다. 그러나, 개발자 측면에서는 에이전트 시스템에서 요구하는 각종 기능 및 제약규칙...