• Title/Summary/Keyword: 윤곽 검출

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자가 생성 지도 학습 알고리즘을 이용한 컨테이너 식별자 인식

  • Kim, Jae-Yong;Park, Chung-Sik;Kim, Gwang-Baek
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2005.11a
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    • pp.500-506
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    • 2005
  • 본 논문에서는 자가 생성 지도 학습 알고리즘을 이용한 운송 컨테이너 식별자 인식 시스템을 제안한다. 일반적으로 운송 컨테이너의 식별자들은 글자의 색이 검정색 또는 흰색으로 이루어져 있는 특정이 있다. 이러한 특성을 고려하여 원 컨테이너 영상에 대해 검은색과 흰색을 제외하고는 모든 부분을 잡음으로 처리하기 위해 퍼지 추론 방법을 이용하여 식별자 영역과 바탕영역을 구별한다. 식별자 영역으로 구분 된 영역은 그대로 두고, 바탕 영역으로 구분된 영역 은 전체 영상의 평균 픽셀 값으로 대체시킨다. 그리고 Sobel 마스크를 이용하여 에지를 검출하고, 추출된 에지를 이용하여 수직 블록과 수평 블록을 검출 하여 컨테이너의 식별자 영역을 추출하고 이진화한다. 이진화 된 식별자 영역에 대해 검정색의 빈도수를 이용하여 흰바탕과 민바탕을 구분하고 4 방향 윤곽선 추적 알고리즘을 적용하여 개별 식별자를 추출 한다. 개별 식별자 인식을 위해 자가 생성 지도 학습 알고리즘을 제안하여 개별 식별자 인식에 적용한다. 제안된 자가 생성 지도 학습 알고리즘은 입력층과 은닉층 사이의 구조를 ART-l을 개선하여 적용하고 은닉층과 출력층 사이에는 일반화된 델타 학습 방법과 Delta-bar-Delta 알고리즘을 적용하여 학습 및 인식 성능을 개선한다. 실제 80 개의 컨테이너 영상을 대상으로 실험한 결과, 제안된 식별자 추출 방법이 이전의 개별 추출 방법보다 추출률이 개선되었고 FCM 기반 자가 생성 지도 학습 알고리즘보다 제안된 자가 생성 지도 학습 알고리즘이 컨테이너 식별자의 학습 및 인식에 있어서 개선된 것을 확인하였다.색 문제를 해결하고자 하는 것이 연구의 목적이다. 정보추출은 사용자의 관심사에 적합한 문서들로부터 어떤 구체적인 사실이나 관계를 정확히 추출하는 작업을 가리킨다.앞으로 e-메일, 매신저, 전자결재, 지식관리시스템, 인터넷 방송 시스템의 기반 구조 역할을 할 수 있다. 현재 오픈웨어에 적용하기 위한 P2P 기반의 지능형 BPM(Business Process Management)에 관한 연구와 X인터넷 기술을 이용한 RIA (Rich Internet Application) 기반 웹인터페이스 연구를 진행하고 있다.태도와 유아의 창의성간에는 상관이 없는 것으로 나타났고, 일반 유아의 아버지 양육태도와 유아의 창의성간의 상관에서는 아버지 양육태도의 성취-비성취 요인에서와 창의성제목의 추상성요인에서 상관이 있는 것으로 나타났다. 따라서 창의성이 높은 아동의 아버지의 양육태도는 일반 유아의 아버지와 보다 더 애정적이며 자율성이 높지만 창의성이 높은 아동의 집단내에서 창의성에 특별한 영향을 더 미치는 아버지의 양육방식은 발견되지 않았다. 반면 일반 유아의 경우 아버지의 성취지향성이 낮을 때 자녀의 창의성을 향상시킬 수 있는 것으로 나타났다. 이상에서 자녀의 창의성을 향상시키는 중요한 양육차원은 애정성이나 비성취지향성으로 나타나고 있어 정서적인 측면의 지원인 것으로 밝혀졌다.징에서 나타나는 AD-SR맥락의 반성적 탐구가 자주 나타났다. 반성적 탐구 척도 두 그룹을 비교 했을 때 CON 상호작용의 특징이 낮게 나타나는 N그룹이 양적으로 그리고 내용적으로 더 의미 있는 반성적 탐구를 했다용을 지원하는 홈페이지를 만들어 자료

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Container Image Recognition using Fuzzy-based Noise Removal Method and ART2-based Self-Organizing Supervised Learning Algorithm (퍼지 기반 잡음 제거 방법과 ART2 기반 자가 생성 지도 학습 알고리즘을 이용한 컨테이너 인식 시스템)

  • Kim, Kwang-Baek;Heo, Gyeong-Yong;Woo, Young-Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.7
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    • pp.1380-1386
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    • 2007
  • This paper proposed an automatic recognition system of shipping container identifiers using fuzzy-based noise removal method and ART2-based self-organizing supervised learning algorithm. Generally, identifiers of a shipping container have a feature that the color of characters is blacker white. Considering such a feature, in a container image, all areas excepting areas with black or white colors are regarded as noises, and areas of identifiers and noises are discriminated by using a fuzzy-based noise detection method. Areas of identifiers are extracted by applying the edge detection by Sobel masking operation and the vertical and horizontal block extraction in turn to the noise-removed image. Extracted areas are binarized by using the iteration binarization algorithm, and individual identifiers are extracted by applying 8-directional contour tacking method. This paper proposed an ART2-based self-organizing supervised learning algorithm for the identifier recognition, which improves the performance of learning by applying generalized delta learning and Delta-bar-Delta algorithm. Experiments using real images of shipping containers showed that the proposed identifier extraction method and the ART2-based self-organizing supervised learning algorithm are more improved compared with the methods previously proposed.

An Automatic ROI Extraction and Its Mask Generation based on Wavelet of Low DOF Image (피사계 심도가 낮은 이미지에서 웨이블릿 기반의 자동 ROI 추출 및 마스크 생성)

  • Park, Sun-Hwa;Seo, Yeong-Geon;Lee, Bu-Kweon;Kang, Ki-Jun;Kim, Ho-Yong;Kim, Hyung-Jun;Kim, Sang-Bok
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.3
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    • pp.93-101
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    • 2009
  • This paper suggests a new algorithm automatically searching for Region-of-Interest(ROI) with high speed, using the edge information of high frequency subband transformed with wavelet. The proposed method executes a searching algorithm of 4-direction object boundary by the unit of block using the edge information, and detects ROIs. The whole image is splitted by $64{\times}64$ or $32{\times}32$ sized blocks and the blocks can be ROI block or background block according to taking the edges or not. The 4-directions searche the image from the outside to the center and the algorithm uses a feature that the low-DOF image has some edges as one goes to center. After searching all the edges, the method regards the inner blocks of the edges as ROI, and makes the ROI masks and sends them to server. This is one of the dynamic ROI method. The existing methods have had some problems of complicated filtering and region merge, but this method improved considerably the problems. Also, it was possible to apply to an application requiring real-time processing caused by the process of the unit of block.

An Analysis of Factors That Affect Image Quality Deterioration in The Potable X-ray Examination on using Digital Wireless Detector (디지털 무선 검출기를 이용한 이동형 X선검사에서 영상품질 저하의 요인분석)

  • Yu, Young-Eun;Lim, Cheong-Hwan;Ko, Joo-Young
    • Journal of radiological science and technology
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    • v.37 no.2
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    • pp.93-100
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    • 2014
  • Recently the development of portable digital wireless imaging system, which acquires digital radiation images by using wireless LAN telecommunications function in an easy and fast way, provides lots of convenience for people. Considering the characteristics of portable imaging tests on emergency and critical patients, this study aims to suggest guidelines for Digital wireless detector by evaluating the effect of de-centering of focus-grid and displacement of subject in detector on the quality of image. The equipments used for this study were Elmo-T6 Digital Mobile X-ray system (SIMAZU Corp.), el' Tor ($14{\times}17$ "Wireless detector), Grid (10:1) and Chest & head phantom. After acquiring post-processing image according to dose increase and de-centering image of grid-focus and head phantom displacement image, this study compared, analyzed and evaluated these images by using a digital image analysis program by Image J. In the change of images based on dose increase, images were rough in the dose of 0.5 mAs, while there was no difference among images in the proper dose of 1~2 mAs and, especially from 2.5 mAs, average value of pixels radically decreased, affecting contrast. Over 3 mAs, contrast dropped due to saturation phenomenon of lungs. As the result of analysis using Image J program, with the increase of displacement between focus-grid and head phantom, the frequency of low pixel value also increase, causing the outline of surface image to disappear, which in turn affects contrast. For better quality imaging, a radiographer must be aware before the time of test that the image quality can be changed based on the critical patient's posture, movement, respiration, displacement of X-ray tube and distance of imaging.

A Study on Measuring Vehicle Length Using Laser Rangefinder (레이저 거리계를 이용한 차량 전장 측정 방법에 관한 연구)

  • Ryu, In-Hwan;Kwon, Jang-Woo;Lee, Sang-Min
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.1
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    • pp.66-76
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    • 2016
  • Determination of type of a vehicle is being used in various areas such as collecting tolls, collecting statistical traffic data and traffic prognosis. Because most of the vehicle type classification systems depend on vehicle length indirectly or directly, highly reliable automatic vehicle length measurement system is crucial for them. This study makes use of a pencil beam laser rangemeter and devises a mechanical device which rotates the laser rangemeter. The implemented system measures the range between a point and the laser rangemeter then indicates it as a spherical coordinate. We obtain several silhouettes of cross section of the vehicle, the rate of change of the silhouettes, signs of the rates then squares the rates to apply cell averaging constant false alarm rate (CA-CFAR) technique to find out where the border is between the vehicle and the background. Using the border and trigonometry, we calculated the length of the vehicle and confirmed that the calculated vehicle length is about 94% of actual length.

Quality Assurance of Multileaf Collimator Using Electronic Portal Imaging (전자포탈영상을 이용한 다엽시준기의 정도관리)

  • ;Jason W Sohn
    • Progress in Medical Physics
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    • v.14 no.3
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    • pp.151-160
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    • 2003
  • The application of more complex radiotherapy techniques using multileaf collimation (MLC), such as 3D conformal radiation therapy and intensity-modulated radiation therapy (IMRT), has increased the significance of verifying leaf position and motion. Due to thier reliability and empirical robustness, quality assurance (QA) of MLC. However easy use and the ability to provide digital data of electronic portal imaging devices (EPIDs) have attracted attention to portal films as an alternatives to films for routine qualify assurance, despite concerns about their clinical feasibility, efficacy, and the cost to benefit ratio. In this study, we developed method for daily QA of MLC using electronic portal images (EPIs). EPID availability for routine QA was verified by comparing of the portal films, which were simultaneously obtained when radiation was delivered and known prescription input to MLC controller. Specially designed two-test patterns of dynamic MLC were applied for image acquisition. Quantitative off-line analysis using an edge detection algorithm enhanced the verification procedure as well as on-line qualitative visual assessment. In conclusion, the availability of EPI was enough for daily QA of MLC leaf position with the accuracy of portal films.

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A Study on Tracking Algorithm for Moving Object Using Partial Boundary Line Information (부분 외곽선 정보를 이용한 이동물체의 추척 알고리즘)

  • Jo, Yeong-Seok;Lee, Ju-Sin
    • The KIPS Transactions:PartB
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    • v.8B no.5
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    • pp.539-548
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    • 2001
  • In this paper, we propose that fast tracking algorithm for moving object is separated from background, using partial boundary line information. After detecting boundary line from input image, we track moving object by using the algorithm which takes boundary line information as feature of moving object. we extract moving vector on the imput image which has environmental variation, using high-performance BMA, and we extract moving object on the basis of moving vector. Next, we extract boundary line on the moving object as an initial feature-vector generating step for the moving object. Among those boundary lines, we consider a part of the boundary line in every direction as feature vector. And then, as a step for the moving object, we extract moving vector from feature vector generated under the information of the boundary line of the moving object on the previous frame, and we perform tracking moving object from the current frame. As a result, we show that the proposed algorithm using feature vector generated by each directional boundary line is simple tracking operation cost compared with the previous active contour tracking algorithm that changes processing time by boundary line size of moving object. The simulation for proposed algorithm shows that BMA operation is reduced about 39% in real image and tracking error is less than 2 pixel when the size of feature vector is [$10{\times}5$] using the information of each direction boundary line. Also the proposed algorithm just needs 200 times of search operation bout processing cost is varies by the size of boundary line on the previous algorithm.

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Studies on the Preservative Condition and the Ultrastructure of Hair of Newly Found Sixteenth Century Mummy in Paju (파주에서 발견된 16세기 미라 머리카락의 미세구조과 보존상태에 관한 연구)

  • Lee, Gwi-Yeong;Chang, Byung-Soo
    • Applied Microscopy
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    • v.35 no.4
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    • pp.24-31
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    • 2005
  • The preservative condition and ultrastructure on the mummified hair collected from newly found female mummy in Paju, were investigated by using scanning and transmission electron microscopes. The female mummy was found in september, 2002 during the traditional reburial process for the buried ones. The hair of 16th century mummy showed very intact appearances during observation with electron microscope. And the structures of the cortex, medulla and cuticle were well preserved. The cuticle layer was easily discernable, which are composed of six to seven cuticular cells. Each cuticular cells surrounded and thus seperated from its neighbors by intercellular membrane complex. In the cortex, many macrofibrils and some melanin granules between them were observed. We observed well preserved rod form macrofibrils running parallel along the direction of hair shaft. Especially, melanin granules were aggregated in the cortex which was adjacent to the cuticlu layer. As to the cause for the well-preservation of 440 year old hair sample, the presence of surface coat on the hair, which are composed of various materials. As calcium was included in the surface coat in Electron Dispersive X-ray Spectroscopy (EDS), the hardening process of the surface coat by calcium might inhibit the water or microorganism infiltration into the hair.

Automatic Tumor Segmentation Method using Symmetry Analysis and Level Set Algorithm in MR Brain Image (대칭성 분석과 레벨셋을 이용한 자기공명 뇌영상의 자동 종양 영역 분할 방법)

  • Kim, Bo-Ram;Park, Keun-Hye;Kim, Wook-Hyun
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.4
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    • pp.267-273
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    • 2011
  • In this paper, we proposed the method to detect brain tumor region in MR images. Our method is composed of 3 parts, detection of tumor slice, detection of tumor region and tumor boundary detection. In the tumor slice detection step, a slice which contains tumor regions is distinguished using symmetric analysis in 3D brain volume. The tumor region detection step is the process to segment the tumor region in the slice distinguished as a tumor slice. And tumor region is finally detected, using spatial feature and symmetric analysis based on the cluster information. The process for detecting tumor slice and tumor region have advantages which are robust for noise and requires less computational time, using the knowledge of the brain tumor and cluster-based on symmetric analysis. And we use the level set method with fast marching algorithm to detect the tumor boundary. It is performed to find the tumor boundary for all other slices using the initial seeds derived from the previous or later slice until the tumor region is vanished. It requires less computational time because every procedure is not performed for all slices.

Pupil Data Measurement and Social Emotion Inference Technology by using Smart Glasses (스마트 글래스를 활용한 동공 데이터 수집과 사회 감성 추정 기술)

  • Lee, Dong Won;Mun, Sungchul;Park, Sangin;Kim, Hwan-jin;Whang, Mincheol
    • Journal of Broadcast Engineering
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    • v.25 no.6
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    • pp.973-979
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    • 2020
  • This study aims to objectively and quantitatively determine the social emotion of empathy by collecting pupillary response. 52 subjects (26 men and 26 women) voluntarily participated in the experiment. After the measurement of the reference of 30 seconds, the experiment was divided into the task of imitation and spontaneously self-expression. The two subjects were interacted through facial expressions, and the pupil images were recorded. The pupil data was processed through binarization and circular edge detection algorithm, and outlier detection and removal technique was used to reject eye-blinking. The pupil size according to the empathy was confirmed for statistical significance with test of normality and independent sample t-test. Statistical analysis results, the pupil size was significantly different between empathy (M ± SD = 0.050 ± 1.817)) and non-empathy (M ± SD = 1.659 ± 1.514) condition (t(92) = -4.629, p = 0.000). The rule of empathy according to the pupil size was defined through discriminant analysis, and the rule was verified (Estimation accuracy: 75%) new 12 subjects (6 men and 6 women, mean age ± SD = 22.84 ± 1.57 years). The method proposed in this study is non-contact camera technology and is expected to be utilized in various virtual reality with smart glasses.