• 제목/요약/키워드: automatic processing

검색결과 2,230건 처리시간 0.041초

Liver Segmentation and 3D Modeling from Abdominal CT Images

  • Tran, Hong Tai;Oh, A Ran;Na, In Seop;Kim, Soo Hyung
    • 스마트미디어저널
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    • 제5권1호
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    • pp.49-54
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    • 2016
  • Medical image processing is a compulsory process to diagnose many kinds of disease. Therefore, an automatic algorithm for this task is highly demanded as an important part to construct a computer-aided diagnosis system. In this paper, we introduce an automatic method to segment the liver region from 3D abdominal CT images using Otsu method. First, we choose a 2D slice which has most liver information from the whole 3D image. Secondly, on the chosen slice, we enhanced the image based on its intensity using Otsu method with multiple thresholds and use the threshold to enhance the whole 3D image. Then, we apply a liver mask to mark the candidate liver region. After that, we execute the Otsu method again to segment the liver region from the chosen slice and propagate the result to the whole 3D image. Finally, we apply preprocessing on the frontal side of 3D images to crop only the liver region from the image.

Research on Water Edge Extraction in Islands from GF-2 Remote Sensing Image Based on GA Method

  • Bian, Yan;Gong, Yusheng;Ma, Guopeng;Duan, Ting
    • Journal of Information Processing Systems
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    • 제17권5호
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    • pp.947-959
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    • 2021
  • Aiming at the problem of low accuracy in the water boundary automatic extraction of islands from GF-2 remote sensing image with high resolution in three bands, new water edges automatic extraction method in island based on GF-2 remote sensing images, genetic algorithm (GA) method, is proposed in this paper. Firstly, the GA-OTSU threshold segmentation algorithm based on the combination of GA and the maximal inter-class variance method (OTSU) was used to segment the island in GF-2 remote sensing image after pre-processing. Then, the morphological closed operation was used to fill in the holes in the segmented binary image, and the boundary was extracted by the Sobel edge detection operator to obtain the water edge. The experimental results showed that the proposed method was better than the contrast methods in both the segmentation performance and the accuracy of water boundary extraction in island from GF-2 remote sensing images.

A Novel Whale Optimized TGV-FCMS Segmentation with Modified LSTM Classification for Endometrium Cancer Prediction

  • T. Satya Kiranmai;P.V.Lakshmi
    • International Journal of Computer Science & Network Security
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    • 제23권5호
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    • pp.53-64
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    • 2023
  • Early detection of endometrial carcinoma in uterus is essential for effective treatment. Endometrial carcinoma is the worst kind of endometrium cancer among the others since it is considerably more likely to affect the additional parts of the body if not detected and treated early. Non-invasive medical computer vision, also known as medical image processing, is becoming increasingly essential in the clinical diagnosis of various diseases. Such techniques provide a tool for automatic image processing, allowing for an accurate and timely assessment of the lesion. One of the most difficult aspects of developing an effective automatic categorization system is the absence of huge datasets. Using image processing and deep learning, this article presented an artificial endometrium cancer diagnosis system. The processes in this study include gathering a dermoscopy images from the database, preprocessing, segmentation using hybrid Fuzzy C-Means (FCM) and optimizing the weights using the Whale Optimization Algorithm (WOA). The characteristics of the damaged endometrium cells are retrieved using the feature extraction approach after the Magnetic Resonance pictures have been segmented. The collected characteristics are classified using a deep learning-based methodology called Long Short-Term Memory (LSTM) and Bi-directional LSTM classifiers. After using the publicly accessible data set, suggested classifiers obtain an accuracy of 97% and segmentation accuracy of 93%.

웹 통합문서의 효율적 생성과 검색을 위한 자동링크지원 시스템의 설계 및 구축 (Design and Implementation of Automatic Linking Support System for Efficient Generating and Retrieving Integrated Documents Based on Web)

  • 이원중;정은재;주수종;이승용
    • 정보처리학회논문지A
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    • 제10A권2호
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    • pp.93-100
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    • 2003
  • 분산 컴퓨팅과 웹 서비스 기술의 발달과 함께, 급증하는 인터넷 사용자는 웹 기반의 맞춤형 정보를 편리하게 작성하고 제공받을 수 있는 서비스들을 요구하고 있다. 이를 위해, 본 논문에서는 맞춤형 정보로서 웹 기반의 통합문서를 생성하고, 사용자 요구에 따라 다양한 검색을 지원할 수 있는 자동링크지원 시스템(ALSS : Automatic Linking Support System)을 구축하고자 한다. 본 시스템의 구성은 클라이언트/서버 환경을 기반으로, 서버는 어휘분석, 질의처리 및 통합문서생성 기능들을 제공하는 자동링크엔진과 사전, 이미지 컨텐츠 및 URLs로 이루어진 데이터베이스를 지원하도록 구축하였다. 클라이언트 측은 서버 측의 자동링크엔진과 데이터베이스를 접근하여 웹 기반의 통합문서를 생성하는 웹 에디터와 검색 서비스를 지원하는 웹 도우미로 구축하였다. 웹 에디터나 웹 도우미 프로그램은 클라이언트 측에 별도의 설치 없이 서버로부터 다운로딩하여 실행할 수 있으며, 서버의 실행기능들의 일부를 글라이언트 측에 분산시키므로써 서버의 부하를 감소시켰다. 본 시스템의 구현으로서, 사용자 인터페이스는 JDK 1.3 기반의 SWING을 이용하고, 클라이언트와 서버간의 연동을 위한 자바 RMI 기법을 적용하였으며, SQL Server 7.0을 사용하여 데이터베이스를 구축하였다. 마지막으로 웹 에디터와 웹 도우미에 의해 자동링크엔진과 데이터베이스를 접근하는 과정과 그들의 실행결과를 보였다.

2차원 바코드와 UCC/EAN-128을 이용한 생물자원 자동인식시스템 (An Automatic Identification System of Biological Resources based on 2D Barcode and UCC/EAN-128)

  • 주민석;류근호;김준우;김흥태;한복기
    • 정보처리학회논문지D
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    • 제15D권6호
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    • pp.861-872
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    • 2008
  • 컴퓨팅 환경이 발전함에 따라 다양한 물리적 객체와 디지털 정보를 연동하는 자동인식 연구가 활발히 진행 중이다. 이러한 자동인식시스템은 다양한 산업분야에서 활용되고 있음에도 불구하고 보건의료와 관련한 자동인식 기술의 접목은 아직까지 다른 산업기술 전반에 미치지 못하고 있는 실정이다. 이에 따라 의료장비, 혈액, 인체조직 등 보건의료 용품의 자동인식에 관한 여러 연구가 진행 중이다. 이 논문은 인간 유전체 연구의 필수 연구재료인 생물자원을 대상으로 자동인식 기술의 적용 방안을 제안한다. 먼저, 자동인식기술 도입을 위해 사용 환경상의 고려사항을 정의하고, 조사과정 또는 실험을 통하여 적합한 형태의 태그 인터페이스로서 바코드를 선택하였다. 바코드 심볼로지는 2차원 바코드 심볼로지인 Data Matrix를 사용하고, 데이터 스키마는 국제적 범용성 추구를 위하여 UCC/EAN-128 기반으로 설계하였다. 제안된 기술들이 실제 환경에 적용되는지를 보이기 위한 어플리케이션을 개발하고, 이에 대한 실험 및 평가를 다음의 방법으로 수행하였다. 생물자원이 실제 보존되는 영하 $196^{\circ}C$, 영하 $75^{\circ}C$의 초저온 보존환경에서 바코드 인식실험을 한 결과 1.6초 내외의 평균 인식시간을 보이며, 데이터 스키마는 생물자원 활용 분야의 요구사항을 만족하는 것으로 평가되었다. 따라서 제안한 방법으로 생물자원의 정보처리 과정에서 정확성과 데이터 입력의 신속성이 제공될 수 있다.

Design of Vision Based Punching Machine having Serial Communication

  • Lee, Young-Choon;Lee, Seong-Cheol;Kim, Seong-Min
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.2430-2434
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    • 2005
  • Automatic FPC punching instrument for the improvement of working condition and cost saving is introduced in this paper. FPC(flexible printed circuit) is used to detect the contact position of K/B and button like a cellular phone. Depending on the quality of the printed ink and position of reference punching point to the FPC, the resistance and current are varied to the malfunctioning values. The size of reference punching point is 2mm and the above. Because the punching operation is done manually, the accuracy of the punching degree is varied with operator's condition. Recently, The punching accuracy has deteriorated severely to the 2mm punching reference hall so that assembly of the K/B has hardly done. To improve this manual punching operation to the FPC, automatic FPC punching system is introduced. Precise mechanical parts like a 5-step stepping motor and ball screw mechanism are designed and tested and low cost PC camera is used for the sake of cost down instead of using high quality vision systems for the FA. 3D Mechanical design tool(Pro/E) is used to manage the exact tolerance circumstances and avoid design failures. Simulation is performed to make the complete vision based punching machine before assembly, and this procedure led to the manufacturing cost saving. As the image processing algorithms, dilation, erosion, and threshold calculation is applied to obtain an exact center position from the FPC print marks. These image processing algorithms made the original images having various noises have clean binary pixels which is easy to calculate the center position of print marks. Moment and Least square method are used to calculate the center position of objects. In this development circumstance, Moment method was superior to the Least square one at the calculation of speed and against noise. Main control panel is programmed by Visual C++ and graphical Active X for the whole management of vision based automatic punching machine. Operating modes like manual, calibration, and automatic mode are added to the main control panel for the compensation of bad FPC print conditions and mechanical tolerance occurring in the case of punch and die reassembly. Test algorithms and programs showed good results to the designed automatic punching system and led to the increase of productivity and huge cost down to law material like FPC by avoiding bad quality.

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Raster Beam에 의한 우편용 4-state 바코드 판독기 구현 및 판독오차 범위의 최소화 방법에 관한 연구 (A Study on Minimization Method of Reading Error Range and Implementation of Postal 4-state Bar Code Reader with Raster Beam)

  • 박문성;송재관;남윤석;김혜규;정희경
    • 한국정보처리학회논문지
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    • 제7권7호
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    • pp.2149-2160
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    • 2000
  • 4-state 바코드는 우편물 자동구분처리 및 우편물류의 정보표현, 전달, 처리가 효과적으로 지원되도록 개발하고 있다. 4-state 바코드에 표현 정보는 우편번호, 배달순서코드, 고객정보 등이 포함되며, 판독의 향상을 위한 오류정정 코드워드를 적용할 수 있다. 본 논문은 우편용 4-state 바코드를 raster beam에 의하여 판독하는 시스템의 개발과 판독오차 범위의 축소 방법을 다룬 것이다. Raster beam 주사에 의한 판독 오차는 단위 구간별 spot 분포의 동일하지 않은 분포로 인하여 발생된다. 이에 따라, 판독오차를 축소하기 위한 방법으로 각 구간 단위로 바의 두께 값을 측정하여 인접돈 바의 평균값 조정 방법을 제안하였으며, 시험결과 거의 99.8%까지 평균 판독오차가 축소됨을 보였다.

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Noise Robust Automatic Speech Recognition Scheme with Histogram of Oriented Gradient Features

  • Park, Taejin;Beack, SeungKwan;Lee, Taejin
    • IEIE Transactions on Smart Processing and Computing
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    • 제3권5호
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    • pp.259-266
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    • 2014
  • In this paper, we propose a novel technique for noise robust automatic speech recognition (ASR). The development of ASR techniques has made it possible to recognize isolated words with a near perfect word recognition rate. However, in a highly noisy environment, a distinct mismatch between the trained speech and the test data results in a significantly degraded word recognition rate (WRA). Unlike conventional ASR systems employing Mel-frequency cepstral coefficients (MFCCs) and a hidden Markov model (HMM), this study employ histogram of oriented gradient (HOG) features and a Support Vector Machine (SVM) to ASR tasks to overcome this problem. Our proposed ASR system is less vulnerable to external interference noise, and achieves a higher WRA compared to a conventional ASR system equipped with MFCCs and an HMM. The performance of our proposed ASR system was evaluated using a phonetically balanced word (PBW) set mixed with artificially added noise.

유전자 알고리즘과 퍼지규칙을 기반으로한 지능형 자동감시 시스템의 개발 (A Fuzzy Logic System for Detection and Recognition of Human in the Automatic Surveillance System)

  • 장석윤;박민식;이영주;박민용
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2001년도 하계종합학술대회 논문집(3)
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    • pp.237-240
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    • 2001
  • An image processing and decision making method for the Automatic Surveillance System is proposed. The aim of our Automatic Surveillance System is to detect a moving object and make a decision on whether it is human or not. Various object features such as the ratio of the width and the length of the moving object, the distance dispersion between the principal axis and the object contour, the eigenvectors, the symmetric axes, and the areas if the segmented region are used in this paper. These features are not the unique and decisive characteristics for representing human Also, due to the outdoor image property, the object feature information is unavoidably vague and inaccurate. In order to make an efficient decision from the information, we use a fuzzy rules base system ai an approximate reasoning method. The fuzzy rules, combining various object features, are able to describe the conditions for making an intelligent decision. The fuzzy rule base system is initially constructed by heuristic approach and then, trained and tasted with input/output data Experimental result are shown, demonstrating the validity of our system.

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방사선 영상을 이용한 탄약신관 안전상태 자동인식기술 개발 (Automatic Safety Inspection Technique for Ammunition Fuzes using Radiographic Images)

  • 안지연
    • 한국군사과학기술학회지
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    • 제18권3호
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    • pp.283-292
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    • 2015
  • This paper presents the development of the automatic safety inspection technique for the ammunition fuzes using radiography images. The technique inspects 49-ammunition fuze by detecting the X-ray or neutron radiographic images to check whether the fuze is unintendedly armed or/and some major assembled parts are at right place. To execute the program, we loads the image(s) for under test. After reading images, the program conducts a series of pre-image processing, and then starts inspecting input images by using the detection algorithms which are designed distinctively for each fuze. After completing the detection process, the program displays the final result of the fuze status: "safety or danger." Through this program, we can cut off the fuzes which have any doubt about safety, and can only provide absolutely safe fuzes, compared with the current naked eye inspection method.