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Foreground detection of moving object using Gaussian mixture model

Nazia Aslam, Veena Sharma

Year
2017
Citations
19

Abstract

The segmentation/Detection of a moving object is one of the important step in computer vision application, such as remote sensing, medical imaging, traffic surveillance, machine/robot vision, microscopic imaging etc. In this paper “Gaussian Mixture model” for background subtraction/foreground detection has been applied which computes a foreground mask on a moving object (which is either the color video frame or series of a gray scale image). The blob analyzer has also been used to calculate statistics of identified region in a binary image. The result shows that the proposed algorithm can detect the moving object effectively while occluded by the box.

Keywords

Background subtractionArtificial intelligenceComputer visionComputer scienceObject detectionMixture modelSegmentationBlob detectionImage segmentationObject-class detection

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