• Title/Summary/Keyword: Feature detection

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Multiple Moving Objects Detection and Tracking Using Snake Model (Snake 모델을 이용한 다중 이동 객체 검출 및 추적)

  • Woo Jang-Myoung;Kim Sung-Dong;Choi Ki-Ho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.2 no.2 s.3
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    • pp.85-95
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    • 2003
  • This paper proposes a multiple moving objects tracking system which is adaptable itself to circumstances. Snake model is sensitive to the start position value because it does not accurately express contours of objects in complex image. It can be improved as the proposed system gets background images by using difference images, segments objects using neighborhood pixels and assesses the position feature values acquired on the start position value to deformable Snake model. And also the system can simplify complex background images and reduce search regions by the constituent points of a Snake laid in Positions of object. It is showed that the proposed system can be appBied to multiple moving vehicle racking systems by the experimental results of 30fps AVI file.

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Pre-processing Faded Measurements for Bearing-and-Frequency Target Motion Analysis

  • Lee, Man-Hyung;Moon, Jeong-Hyun;Kim, In-Soo;Kim, Chang-Sup;Choi, Jae-Weon
    • International Journal of Control, Automation, and Systems
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    • v.6 no.3
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    • pp.424-433
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    • 2008
  • An ownship with towed array sonar (TAS) has limited maneuvers due to its dynamic feature, bearing and frequency measurements of a target which are not detected continuously but are often lost in ocean environment. We propose a pre-processing algorithm for the faded bearing and frequency measurements to solve the BFTMA problem of TAS under limited detection conditions. The proposed pre-processing algorithm to restore the faded bearing and frequency measurements is implemented to perform a BFTMA filter even if the measurements of a target are not continuously detected. The Modified Gain Extended Kalman Filter (MGEKF) method based on the Interacting Multiple Model (IMM) structure is applied for a BFTMA filter algorithm to estimate the target. Simulations for the various conditions were carried out to verify the applicability of the proposed algorithms, and confirmed superior estimation performance compared with the existing Bearings-Only TMA (BOTMA).

Implementation of Pedestrian Recognition Based on HOG using ROI for Real Time Processing (실시간 처리를 위한 ROI가 적용된 HOG 기반 보행자 인식 구현)

  • Lee, Joo-Young
    • Journal of IKEEE
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    • v.18 no.4
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    • pp.581-585
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    • 2014
  • In this paper, we propose a pedestrian detection by applying the HOG feature using ROI. Conventional HOG method has high accuracy, but shows the disadvantage of slow processing speed. By applying the ROI to the conventional method reduce computations for unnecessary area. Therefore proposed method improves the processing speed. In order to set the ROI area, we propose a structure that combined odd frames and even frames. Odd frame is in charge of operation for the entire area. And even frame does the operation for the ROI area. Implementation results of proposed method maintaining the same accuracy as the conventional method show a 20% improved performance of 8.3 frames per second.

Effective real-time identification using Bayesian statistical methods gaze Network (베이지안 통계적 방안 네트워크를 이용한 효과적인 실시간 시선 식별)

  • Kim, Sung-Hong;Seok, Gyeong-Hyu
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.3
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    • pp.331-338
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    • 2016
  • In this paper, we propose a GRNN(: Generalized Regression Neural Network) algorithms for new eyes and face recognition identification system to solve the points that need corrective action in accordance with the existing problems of facial movements gaze upon it difficult to identify the user and. Using a Kalman filter structural information elements of a face feature to determine the authenticity of the face was estimated future location using the location information of the current head and the treatment time is relatively fast horizontal and vertical elements of the face using a histogram analysis the detected. And the light obtained by configuring the infrared illuminator pupil effects in real-time detection of the pupil, the pupil tracking was - to extract the text print vector.

Feature Detection of Signals using Wavelet Spectrum Analysis (웨이브렛 스펙트럼 분석을 이용한 신호의 특징 검출)

  • Bae Sang-Bum;Kim Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.4
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    • pp.758-763
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    • 2006
  • In various fields of basic science and engineering, in order to present signals and systems exactly and acquire useful information from spatial and timely changes, many researches have been processed. In these methods, the Fourier transform which represents signal as the combination of the frequency component has been applied to the most fields. But as transform not to consider time information, the Fourier transform has its limitations of application. To overcome this problem, a variety of methods including the wavelet transform have been proposed. As transform to represent signal by using the changing window, according to scale parameter in time-scale domain, the wavelet transform is capable of multiresolution analysis and defines various functions according to the application environments. In this paper, to detect features of signal we analyzed wavelet the spectrum by using the basis function of the fourier transform.

The Relationship between the Expression of Melanoma Differentiation-Associated Gene-7/Interleukin-24 (MDA-7/IL-24) and Clinicopathological Features in Colorectal Adenocarcinomas

  • Seo, Boram;Hong, Young Seob;Youngmin, Youngmin;Roh, Mee Sook
    • Biomedical Science Letters
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    • v.18 no.4
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    • pp.413-419
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    • 2012
  • The melanoma differentiation-associated gene-7 (MDA-7) protein, also known as interleukin-24 (IL-24), is a novel candidate of tumor suppressor that can induce apoptosis experimentally in a variety of human malignant cells. However, there have been few studies about its role in colorectal cancer. We performed immunohistochemical detection of MDA-7/IL-24 in 399 tissue samples from primary colorectal adenocarcinoma patients using a tissue microarray. Western blotting was then done to confirm the immunohistochemical observations. MDA-7/IL-24 immunoreactivity was observed in 116 (29.1%) of the 399 colorectal adenocarcinoma cases. Analysis of the MDA-7/IL-24 expression by Western blotting confirmed the immunohistochemical results. The tumors with a negative MDA-7/IL-24 expression more frequently showed poor differentiation (P=0004), lymph node metastasis (P=0.001), deep invasion (P=0.008) and high stage (P=0.001). A subset of colorectal adenocarcinoma revealed a decreased expression of MDA-7/IL-24, and this was associated with progressive pathologic features. These findings suggest that loss of MDA-7/IL-24 expression may play a role in tumor growth and progression of colorectal adenocarcinomas.

Region Detection Using the Feature Point Extraction from Medical Image (의료영상에서 특징점 추출을 이용한 영역추출)

  • 김엄준;성미영
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.429-431
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    • 1998
  • 본 논문에서는 의료 영상 중에서 성대 운동의 불규칙적인 움직임을 판단하여 자동으로 진단 파라미터를 구하는 비디오스트로보키모그래피(Videostrobokymography) 시스템에서 관심 영역을 추출하는 방법을 소개하고자 한다. CCD카메라에 의해 촬영된 영상은 비디오 테이프에 저장된 후 이미지 캡쳐 보드에서 그레이 이미지(gray-level)로 변환되어 저장된다. 입력된 영상은 움직이는 영상을 촬영한 것이므로 관심 영역의 위치가 각 프레임마다 다르다. 또한 실제로 입력된 성대영상들이 점진적인 농도 변화를 보이기 때문에 에지에 의해 영역을 추출하는 일반적인 영역 추출방법은 사용하기 어렵다. 본 논문에서는 두 번의 단계를 통하여 관심 영역을 추출하고 있다. 첫 번째는 입력된 영상에서 노이즈를 제거한 후 각 프레임에서 영상의 최소 에너지를 구한다. 두 번째로 농도 변화 값을 특징 값으로 이용하는 분할-합병 알고리즘(Split-merge Algorithm)을 적용하여 관심 영역을 추출하였다. 제안한 알고리즘을 19명의 성대 영상에 적용하여 분석한 결과 성대의 관심 영역을 추출할 수 있었다. 그리고, 영상의 에너지 값을 이용하는 스네이크 알고리즘(Snake Algorithm)에 적용하여 비교해본 결과 본 연구에서 제안하는 스네이크 알고리즘보다 좋은 성능을 보임을 확인할 수 있었다. 본 연구에서 제안하는 관심 영역 추출 방법은 동적인 변화를 보이는 영상에서 관심 영역을 추출할 수 있을 뿐 아니라 계산 량이 적어 200x280크기의 이미지를 초당 약 40프레임에 대한 관심 영역을 추출할 수 있는 장점이 있다.

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Content Adaptive Interpolation for Intra-field Deinterlacting (공간적 디인터레이싱을 위한 컨텐츠 기반 적응적 보간 기법)

  • Kim, Won-Ki;Jin, Soon-Jong;Jeong, Je-Chang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.10C
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    • pp.1000-1009
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    • 2007
  • This paper presents a content adaptive interpolation (CAI) for intra deinterlacing. The CAI consists of three steps: pre-processing, content classification, and adaptive interpolation. There are also three main interpolation methods in our proposed CAI, i.e. modified edge-based line averaging (M-ELA), gradient directed interpolation (GDI), and window matching method (WMM). Each proposed method shows different performances according to spatial local features. Therefore, we analyze the local region feature using the gradient detection and classify each missing pixel into four categories. And then, based on the classification result, a different do-interlacing algorithm is activated in order to obtain the best performance. Experimental results demonstrate that the CAI method performs better than previous techniques.

A Robust Method for Automatic Segmentation and Recognition of Apoptosis Cell (Apoptosis 세포의 자동화된 분할 및 인식을 위한 강인한 방법)

  • Liu, Hai-Ling;Shin, Young-Suk
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.6
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    • pp.464-468
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    • 2009
  • In this paper we propose an image-based approach, which is different from the traditional flow cytometric method to detect shape of apoptosis cells. This method can overcome the defects of cytometry and give precise recognition of apoptosis cells. In this work K-means clustering was used to do the rough segmentation and an active contour model, called 'snake' was used to do the precise edge detection. And then some features were extracted including physical feature, shape descriptor and texture features of the apoptosis cells. Finally a Mahalanobis distance classifier classifies the segmentation images as apoptosis and non-apoptosis cell.

DETECTION AND CLASSIFICATION OF DEFECTS ON APPLE USING MACHINE VISION

  • Suh, Sang-Ryong;Sung, Je-Hoon
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1996.06c
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    • pp.852-862
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    • 1996
  • This study was carried out to develop tools to detect defects of apple using machine vision. For the purpose, 6 kinds of frame for color images, R, G, B, h, S, and I frame, and a frame for near infra-red images (NIR frame) were tested first to select one which is useful to segment defect areas from apple images. After then, several methods to classify kind of defect for the segmented defect areas were developed and tested. Five kinds of apple defect -bruise , decay ,fleck worm hole and scar were investigated . The results are as follows: NIR frame was selected as the best one among the 7 kinds of image frame, and R, G and I frames showed favourable result to segment areas of apple defect. Various features of the segmented defect areas were measured to classify the defect areas. Eight kids of feature of the areas-size, roundness, axes length ratio, mean and variance of pixel values, variance of real part of spectrum, mean and variance of power spectrum resulted from spacial ourier transform were observed for the segmented defect areas in the selected 4 frames. then procedures to classify defects using the features were developed for the 4 frames and tested with 75-113 defects on apples. The test resulted that NIR and I frames showed high accuracies to classify the kind of defect as 77% and 76% , respectively.

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