Smart Objects Identification System for Robotic Surveillance

作     者：Amir Akramin Shafie Azhar Bin Mohd Ibrahim Muhammad Mahbubur Rashid 

作者机构：Department of Mechatronics EngineeringFaculty of EngineeringInternational Islamic University Malaysia 

出 版 物：《International Journal of Automation and computing》 (国际自动化与计算杂志（英文版）)

年 卷 期：2014年第11卷第1期

页      面：59-71页

核心收录：

学科分类：080202[工学-机械电子工程] 08[工学] 080203[工学-机械设计及理论] 0804[工学-仪器科学与技术] 0802[工学-机械工程] 

基　　金：the IIUM for supporting 

主　　题：Humans and cars identifcation partially occluded human afne moment invariants video surveillance systems machine vision 

摘      要：Video surveillance is an active research topic in computer *** this paper,humans and cars identifcation technique suitable for real time video surveillance systems is *** technique we proposed includes background subtraction,foreground segmentation,shadow removal,feature extraction and *** feature extraction of the extracted foreground objects is done via a new set of afne moment invariants based on statistics method and these were used to identify human or *** the partial occlusion occurs,although features of full body cannot be extracted,our proposed technique extracts the features of head *** proposed technique can identify human by extracting the human head-shoulder up to 60%–70%***,it has a better classifcation to solve the issue of the loss of property arising from human occluded easily in practical *** whole system works at approximately 16 29 fps and thus it is suitable for real-time *** accuracy for our proposed technique in identifying human is very good,which is 98.33%,while for cars identifcation,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 efective and has strong robustness.