• Journal of Multimedia Information System
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• 제4권4호
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• pp.239-242
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• 2017

This paper proposes a low-cost method for counting people based on blob detection and blob tracking. Here background subtraction is used to detected blob and then the blob is classified with its width and height to specify that the blob is a person. In this system we first define the area of entry and exit point in the video frame. The counting of people starts when midpoint of the people blob crosses the defined point. Finally, total number of people entry and exit from the place is displayed. Experiment result of this proposed system has high accuracy in real-time performance.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2009년도 춘계 종합학술대회 논문집
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• pp.23-29
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• 2009

Blob detection is an essential ingredient process in some computer applications such as intelligent visual surveillance. However, previous blob detection algorithms are still computationally heavy so that supporting real-time multi-channel intelligent visual surveillance in a workstation or even one-channel real-time visual surveillance in a embedded system using them turns out prohibitively difficult. In this paper, we propose a fast and precise blob detection algorithm for visual surveillance. Blob detection in visual surveillance goes through several processing steps: foreground mask extraction, foreground mask correction, and connected component labeling. Foreground mask correction necessary for a precise detection is usually accomplished using morphological operations like opening and closing. Morphological operations are computationally expensive and moreover, they are difficult to run in parallel with connected component labeling routine since they need much different processing from what connected component labeling does. In this paper, we first develop a fast and precise foreground mask correction method utilizing on neighbor pixel checking which is also employed in connected component labeling so that the developed foreground mask correction method can be incorporated into connected component labeling routine. Through experiments, it is verified that our proposed blob detection algorithm based on the foreground mask correction method developed in this paper shows better processing speed and more precise blob detection.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권4호
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• pp.284-290
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• 2013

Feature detection is very important to image processing area. In this paper we compare and analyze some characteristics of image processing algorithms for corner and blob feature detection. We also analyze the simulation results through image matching process. We show that how these algorithms work and how fast they execute. The simulation results are shown for helping us to select an algorithm or several algorithms extracting corner and blob feature.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2002년도 학술대회지
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• pp.307-310
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• 2002

A two-dimensional numerical method for inviscid two-fluid flows with evolution of density interface is developed, and an initially stationary two-dimensional fluid sheet surrounded by another fluid is studied. The Interface between two fluids is modeled as a vertex sheet, and the flow field u÷th the evolution of interface is solved by using vortex-in-cell/front-tracking method. The edge of the sheet Is pulled back into the sheet due to surface tension and a blob is formed at the edge. This blob and fluid sheet are connected by a thin neck. In the inviscid limit, such process of the blob and neck formation is examined in detail and their kinematic characteristics are summarized with dimensionless parameters. The edge recedes at $V=1.06({\sigma}/{\rho}h)^{0.5}$ and the capillary wave Propagating into the fluid sheet must be considered for bettor understanding of the edge receding.

• 한국멀티미디어학회논문지
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• 제17권4호
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• pp.420-432
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• 2014

In detection of moving objects from video sequences, an essential process for intelligent visual surveillance, the cast shadows accompanying moving objects are different from background so that they may be easily extracted as foreground object blobs, which causes errors in localization, segmentation, tracking and classification of objects. Most of the previous research results about moving cast shadow detection and removal usually utilize color information about objects and scenes. In this paper, we proposes a novel cast shadow removal method of moving objects in gray level video data for visual surveillance application. The proposed method utilizes observations about edge patterns in the shadow region in the current frame and the corresponding region in the background scene, and applies Laplacian edge detector to the blob regions in the current frame and the corresponding regions in the background scene. Then, the product of the outcomes of application determines moving object blob pixels from the blob pixels in the foreground mask. The minimal rectangle regions containing all blob pixles classified as moving object pixels are extracted. The proposed method is simple but turns out practically very effective for Adative Gaussian Mixture Model-based object detection of intelligent visual surveillance applications, which is verified through experiments.

• 한국산업정보학회논문지
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• 제19권6호
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• pp.43-51
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• 2014

TFT-LCD 영상은 다양한 특성의 결함을 포함하고 있다. 배경 영역과의 휘도 차이가 커서 육안으로 식별 가능한 결함부터 휘도 차이가 매우 적어서 육안 검출이 어려운 한도성 결함까지 포함한다. 본 논문에서는 휘도 차이를 이용하여 결함 영역에 포함될 확률이 높은 결함 화소부터 순차적으로 단계를 진행하면서 결함 후보 화소를 검출하고, 검출된 후보 화소를 블랍으로 구성하여 블랍의 크기와 주변 영역과의 휘도차이를 이용한 기법을 통해 최종적으로 결함 영역과 잡음을 구분하여 검출하는 알고리즘을 제안한다. 제안한 알고리즘의 타당성을 확인하기 위해 다양한 결함을 포함하는 영상에 대한 실험 결과를 살펴봄으로써 신뢰도 높은 결함 검출 결과를 입증하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.177-179
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• 2005

This paper suggests a high-speed blurred blob image inspection algorithm. When we inspect some products using high-resolution camera, the detected blob images usually have severe blur. And the blur makes it hard to detect an object. There are many blur-processing algorithms, but most of them have no real-time property for high-speed applications at all. In this paper, an MMX technology based algorithm is suggested. The suggested algorithm was found to be effective to detect the blurred blob images via many simulations and long time real-plant experiments.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.331-336
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• 1986

Because the threshold technique using the histogram of intensity is the most attractive for segmentation in the sense of fast image processing, this paper defined the new function of inverse histogram of intensity and found out a threshold by means of it. The segmented errors are removed by regulating a scan size of blob coloring. Blob-coloring algorithm presented by [6] was reproved for good performance i.e., no change of feature in bolobs after blob coloring. The ratio of successful recognition was about 85 percents.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2003년도 하계학술대회 논문집
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• pp.30-33
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• 2003

영상 검지기를 통한 차량 탐지 방법은 날씨와 같은 환경에 민감하게 반응하여 차량의 미탐지 및 오탐지가 발생하게 된다. 이를 해결하기 위해 다양한 일기조건하에서 차량 추적 방법에 대해 제안한다. 다양한 일기 조건하에서의 차량 추적은 눈, 비, 안개 환경에서 각 날씨의 특징을 분석, 반영하여 차량을 탐지하고 추적한다. 눈이 내리는 환경에서는 눈이 카메라 가까이에서 차량 blob으로 잘못 탐지되는 blob을 제거하기 위해 카메라와의 거리에 따른 실제 크기를 구하는 size filtering 방법을 사용한다. 비, 안개 환경에서는 흐릿해진 영상 때문에 차량이 교통신호등에 의해 차량 정체시 여러 차량이 하나의 blob으로 탐지되는 문제점을 해결하기 위해 이전 영상에서의 차량 위치 정보를 이용한 재 blob화 방법을 사용한다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 춘계학술대회
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• pp.519-521
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• 2015

세라믹 소재 영상에서 결함 영역이 다른 영역보다 명암도가 밝게 나타나는 정보를 이용하여 ROI 영역을 추출한다. 추출된 ROI 영역에서 Blurring 기법을 적용하여 미세 잡음을 제거한다. 미세 잡음이 제거된 ROI 영역에서 Median Filter기법을 적용하여 임펄스 잡음을 제거한다. 임펄스 잡음이 제거된 영역에서 Prewit Mask을 적용하여 수평과 수직 에지를 검출하고 검출된 에지에 윤곽선 추적 기법을 적용하여 결함 영역의 경계를 보정한다. 보정된 영상에서 Blob Labeling 기법을 적용하여 최종적으로 결함 영역을 추출한다. 제안된 방법을 8mm와 10mm 세라믹 소재 영상을 대상으로 실험한 결과, 기존의 결함 검출 방법보다 제안된 검출 방법의 검출 성능이 개선된 것을 확인하였다.