期刊名称：International Journal of Early Childhood Special Education
电子版ISSN：1308-5581
出版年度：2022
卷号：14
期号：3
页码：5378-5387
DOI：10.9756/INT-JECSE/V14I3.701
语种：English
出版社：International Journal of Early Childhood Special Education
摘要：Finding toing and froing of objects for security surveillance using Machine Learning algorithms ViBe algorithm compared with HOG algorithm. Materials and Methods:ViBe algorithm and HOG algorithm with sample size (N=32) were iterated 10 times to detect the object accuracy. Finding toing and froing of objects for security surveillance includes the detection of objects from previous historical data. Results: Finding toing and froing of objects for security surveillance using ViBealgorithm (96.81%) and HOG algorithm (91.86%) is obtained. There was a statistical significance between ViBe algorithm and HOG algorithm (p=0.005). For each algorithm, 20 samples iterated and G power were calculated as actual power of 80% and alpha value set as 0.025. Conclusion: Finding toing and froing of objects for security surveillance using ViBe algorithm appears to be significantly better than HOG algorithm with improved accuracy.
关键词：Novel Object Detection;Machine Learning;ViBe Algorithm;HOG algorithm;Toing and Froing;Security Surveillance
