An adaptive center of mass detection system employing a 2-D dynamic element matching algorithm for object tracking

Author(s):  
A. Fish ◽  
D. Akselrod ◽  
O. Yadid-Pecht

An object tracking increases loads of enthusiasm for dynamic research in applications such as video surveillance, vehicle navigation, highways, crowded public places, borders, forest and traffic monitoring areas. The system we develop aims to measure and analyze the application of background subtraction method and block matching algorithm to trace object movements through video-based. The making of video surveillance systems “smart” requires fast, reliable and robust algorithms for moving object detection and tracking. This research applies background subtraction method to detect moving object, assisted with block matching algorithm which aims to get good results on objects that have been detected. Performance evaluation is carried out to determine the various parameters. In this paper author design and develop a novel algorithm for moving object tracking in video surveillance also compares and analyse existing algorithms for moving object tracking. Author main aim to design and develop an algorithm for moving object tracking to handle occlusion and complex object shapes.


2013 ◽  
Vol 341-342 ◽  
pp. 597-600
Author(s):  
Xin Wei ◽  
Guang Feng Chen ◽  
Lin Lin Zhai ◽  
Qing Qing Huang

In order to complete the automated sorting, the manipulator needs the accurate coordinate and angle information of the biscuits. This article design a machine vision based online biscuit detection system. Devise the hardware structure and control logic. Base on geometric matching algorithm, develop the detection software with NI Vision. The software could acquire video to analysis to get the coordinates of biscuits, and update and exchange the data with manipulator control software. The system has been tested to achieve a complete detection rate about 96%.


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