• Title/Summary/Keyword: Subtraction image

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Digital Subtraction Technique for Intravenous X-ray Image System (컴퓨터 영상처리 방식을 이용한 정맥내 혈관 조영술 시스템 개발)

  • 이승지;이태수
    • Journal of Biomedical Engineering Research
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    • v.2 no.2
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    • pp.109-116
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    • 1981
  • The objective of this research is to develop the hardware and software systenls of the digital intravenous angiographic system. The system will be used in clinical diagnosis of cardiovascular and cerebrovascular diseases. By utilizing computer image processing technique and digital subtraction method, the system can decrease the patient's harzard and expenses in performing intravenous angiography, as compared with conventional angiograms of the arterial injection.

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RGB Motion Segmentation using Background Subtraction based on AMF

  • Kim, Yoon-Ho
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.6 no.2
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    • pp.81-87
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    • 2013
  • Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter (AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

RGB Motion Segmentation using Background Subtraction based on AMF

  • Kim, Yoon-Ho
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.7 no.1
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    • pp.61-67
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    • 2014
  • Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter(AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

Periodontal Disease Segmentation by Geometric Analysis (기하학적 분석을 이용한 자연치아 주위염 분리에 관한 연구)

  • Han Sang-hoon;Ahn Yonghak
    • Journal of the Korea Society of Computer and Information
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    • v.9 no.4 s.32
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    • pp.133-139
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    • 2004
  • In this paper. we propose a medical image processing method for detection of periodontal disease by geometric analysis on dental digital radiography. This paper proposes the method of an automatic image alignment and detection of minute changes, to overcome defects in the conventional subtraction radiography by image processing technique, that is necessary for getting subtraction image and ROI(Region Of Interest) focused on a selection method using the geometric features in target images. Therefore, we use these methods because they give accuracy, consistency and objective information or data to results. In result, easily and visually we can identify minute differences in the affected parts whether they have problems or not, and using application system.

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Extracting Blood Vessels through Similarity Analysis and Intensity Correction (유사도 분석과 명암 보정을 통한 혈관 추출)

  • Jang Seok-Woo
    • Journal of Internet Computing and Services
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    • v.7 no.4
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    • pp.33-43
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    • 2006
  • This paper proposes a method to extract coronary arteries effectively in the angiography, In general. DSA(Digital Subtraction Angiography) is a well-established technique for the visualization of coronary arteries, DSA involves the subtraction of a mask image, an image of a heart before the injection of contrast medium, from a live image, However, this technique is sensitive to the movement of background and can cause wrong detection due to the variance of background intensity between two images. Therefore, this paper solves the structural problem resulted from background movement by selecting an image which has the least difference of movement through the similarity analysis of background texture, and it extracts only the blood vessels effectively through local intensity correction of the selected images, Experimental results show that the proposed method has the lower false-detection rate and higher accuracy rate than existing methods.

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Probabilistic Background Subtraction in a Video-based Recognition System

  • Lee, Hee-Sung;Hong, Sung-Jun;Kim, Eun-Tai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.4
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    • pp.782-804
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    • 2011
  • In video-based recognition systems, stationary cameras are used to monitor an area of interest. These systems focus on a segmentation of the foreground in the video stream and the recognition of the events occurring in that area. The usual approach to discriminating the foreground from the video sequence is background subtraction. This paper presents a novel background subtraction method based on a probabilistic approach. We represent the posterior probability of the foreground based on the current image and all past images and derive an updated method. Furthermore, we present an efficient fusion method for the color and edge information in order to overcome the difficulties of existing background subtraction methods that use only color information. The suggested method is applied to synthetic data and real video streams, and its robust performance is demonstrated through experimentation.

Comparison of Two Methods for Stationary Incident Detection Based on Background Image

  • Ghimire, Deepak;Lee, Joonwhoan
    • Smart Media Journal
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    • v.1 no.3
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    • pp.48-55
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    • 2012
  • In general, background subtraction based methods are used to detect the moving objects in visual tracking applications. In this paper we employed background subtraction based scheme to detect the temporarily stationary objects. We proposed two schemes for stationary object detection and we compare those in terms of detection performance and computational complexity. In the first approach we used single background and in the second approach we used dual backgrounds, generated with different learning rates, in order to detect temporarily stopped object. Finally, we used normalized cross correlation (NCC) based image comparison to monitor and track the detected stationary object in a video scene. The proposed method is robust with partial occlusion, short time fully occlusion and illumination changes, as well as it can operate in real time.

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A Study on the Revised Method using Normalized RGB Features in the Moving Object Detection by Background Subtraction (배경분리 방법에 의한 이동 물체 검출에서 개선된 색정보 정규화 기법에 관한 연구)

  • Park, Jong-Beom
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.12 no.6
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    • pp.108-115
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    • 2013
  • A developed skill of an intelligent CCTV is also advancing by using its Image Acquisition Device. In this field, area for technique can be divided into Foreground Subtraction which detects individuals and objects in a potential observing area and a tracing technology which figures out moving route of individuals and objects. In this thesis, an improved algorism for a settled engine development, which is stable to change in both noise and illumination for detecting moving objects is suggested. The proposed algorism from this thesis is focused on designing a stable and real time processing method which is perfect model in detecting individuals, animals, and also low-speeding transports and catching a change in an illumination and noise.

Multiple Moving Object Detection Using Different Algorithms (이종 알고리즘을 융합한 다중 이동객체 검출)

  • Heo, Seong-Nam;Son, Hyeon-Sik;Moon, Byungin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.9
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    • pp.1828-1836
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    • 2015
  • Object tracking algorithms can reduce computational cost by avoiding computation over the whole image through the selection of region of interests based on object detection. So, accurate object detection is an important task for object tracking. The background subtraction algorithm has been widely used in moving object detection using a stationary camera. However, it has the problem of object detection error due to incorrect background modeling, whereas the method of background modeling has been improved by many researches. This paper proposes a new moving object detection algorithm to overcome the drawback of the conventional background subtraction algorithm by combining the background subtraction algorithm with the motion history image algorithm that is usually used in gesture detection. Although the proposed algorithm demands more processing time because of time taken for combining two algorithms, it meet the real-time processing requirement. Moreover, experimental results show that it has higher accuracy compared with the previous two algorithms.