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  1. International Journal of Automation and Computing
  2. International Journal of Automation and Computing : Volume 11
  3. International Journal of Automation and Computing : Volume 11, Issue 1, February 2014
  4. Smart Objects Identification System for Robotic Surveillance
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International Journal of Automation and Computing : Volume 14
International Journal of Automation and Computing : Volume 13
International Journal of Automation and Computing : Volume 12
International Journal of Automation and Computing : Volume 11
International Journal of Automation and Computing : Volume 11, Issue 6, December 2014
International Journal of Automation and Computing : Volume 11, Issue 5, October 2014
International Journal of Automation and Computing : Volume 11, Issue 4, August 2014
International Journal of Automation and Computing : Volume 11, Issue 3, June 2014
International Journal of Automation and Computing : Volume 11, Issue 2, April 2014
International Journal of Automation and Computing : Volume 11, Issue 1, February 2014
Multi-agent Control of High Redundancy Actuation
A Progressive Deployment Strategy for Cooperative Adaptive Cruise Control to Improve Traffic Dynamics
A Hybrid Time-delay Prediction Method for Networked Control System
Developing Bi-CG and Bi-CR Methods to Solve Generalized Sylvester-transpose Matrix Equations
N4SID and MOESP Algorithms to Highlight the Ill-conditioning into Subspace Identification
An Integrated Approach to Hypersonic Entry Attitude Control
Modeling and H $_{∞}$ Robust Control of a Smart Structure with Rate-dependent Hysteresis Nonlinearity
Smart Objects Identification System for Robotic Surveillance
GLCM Based Extraction of Flame Image Texture Features and KPCA-GLVQ Recognition Method for Rotary Kiln Combustion Working Conditions
Image Dehazing Based on Haziness Analysis
Joint Resource Allocation for Lifetime-aware Cooperative Multi-carrier DF System
An Efficient Hop Count Routing Protocol for Wireless Ad Hoc Networks
Control Schemes for Passive Teleoperation Systems over Wide Area Communication Networks with Time Varying Delay
A Multi-dimensional Index Structure Based on Improved VA-file and CAN in the Cloud
Erratum to: An Analysis on Decentralized Adaptive MAC Protocols for Cognitive Radio Networks
International Journal of Automation and Computing : Volume 10
International Journal of Automation and Computing : Volume 9
International Journal of Automation and Computing : Volume 8
International Journal of Automation and Computing : Volume 7
International Journal of Automation and Computing : Volume 6
International Journal of Automation and Computing : Volume 5
International Journal of Automation and Computing : Volume 4
International Journal of Automation and Computing : Volume 3
International Journal of Automation and Computing : Volume 2
International Journal of Automation and Computing : Volume 1

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Smart Objects Identification System for Robotic Surveillance

Content Provider Springer Nature Link
Author Shafie, Amir Akramin Ibrahim, Azhar Bin Mohd Rashid, Muhammad Mahbubur
Copyright Year 2014
Abstract Video surveillance is an active research topic in computer vision. In this paper, humans and cars identification technique suitable for real time video surveillance systems is presented. The technique we proposed includes background subtraction, foreground segmentation, shadow removal, feature extraction and classification. The feature extraction of the extracted foreground objects is done via a new set of affine moment invariants based on statistics method and these were used to identify human or car. When the partial occlusion occurs, although features of full body cannot be extracted, our proposed technique extracts the features of head shoulder. Our proposed technique can identify human by extracting the human head-shoulder up to 60%–70% occlusion. Thus, it has a better classification to solve the issue of the loss of property arising from human occluded easily in practical applications. The whole system works at approximately 16–29 fps and thus it is suitable for real-time applications. The accuracy for our proposed technique in identifying human is very good, which is 98.33%, while for cars’ identification, the accuracy is also good, which is 94.41%. The overall accuracy for our proposed technique in identifying human and car is at 98.04%. The experiment results show that this method is effective and has strong robustness.
Starting Page 59
Ending Page 71
Page Count 13
File Format PDF
ISSN 14768186
Journal International Journal of Automation and Computing
Volume Number 11
Issue Number 1
e-ISSN 17518520
Language English
Publisher Springer-Verlag
Publisher Date 2015-03-12
Publisher Place Berlin, Heidelberg
Access Restriction Subscribed
Subject Keyword Humans and cars identification partially occluded human affine moment invariants video surveillance systems machine vision Control, Robotics, Mechatronics Computer Applications Computer-Aided Engineering (CAD, CAE) and Design
Content Type Text
Resource Type Article
Subject Applied Mathematics Control and Systems Engineering Modeling and Simulation Computer Science Applications
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