Title: Novel Enhanced Particle Filters Approach for Moving Object Detection in Video Surveillance System
Abstract: Video tracking is very essential task in many applications of computer vision such as surveillance, vehicle navigation, autonomous robot navigation etc. Object detection and tracking are important and challenging tasks. Video surveillance in a dynamic environment, especially for humans and vehicles, is one of the current challenging research topics in computer vision. It is a key technology to fight against terrorism, crime, public safety and for efficient management of traffic. It contains detection of interesting moving objects and tracking of such objects from frame to frame. Its main task is to find and follow a moving object or multiple objects in image sequences. Normally there are three stages of video analysis; object detection, object tracking, and object reorganization. This paper presents The main objective of the proposed work is to detect the moving objects with less complexity and accuracy using frame differencing method. First background subtraction is detected using recursive technique. Then noises are removed by Morphological filter and YCbCr Color space for foreground object. In order to obtain accurate detection, Novel Enhanced Particle Filters (NEPF) approach is used. Finally the experimental results show that this method can reduce complexity and generate accurate image without any noises
Publication Year: 2018
Publication Date: 2018-01-01
Language: en
Type: article
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