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Geometric invariant features for the detection and analysis of vehicle

The intelligent traffic management system (ITS) is one of the active research areas. Vehicle detection is a major role in traffic analysis. In the paper, analysis of detecting vehicles is proposed based on the features posed by the vehicle. The foreground pixels from image are extracted by histogram...

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Detalles Bibliográficos
Autores principales: Anandhalli, Mallikarjun, Tanuja, A., Baligar, Pavana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9018969/
https://www.ncbi.nlm.nih.gov/pubmed/35463223
http://dx.doi.org/10.1007/s11042-022-12919-8
Descripción
Sumario:The intelligent traffic management system (ITS) is one of the active research areas. Vehicle detection is a major role in traffic analysis. In the paper, analysis of detecting vehicles is proposed based on the features posed by the vehicle. The foreground pixels from image are extracted by histogram based foreground segmentation. After segmenting, Hu-Moments and Eigen values features are extracted and normalized. The classifiers are trained with the extracted Hu-Moments and Eigen values. The experiments are conducted on different benchmark datasets, and results are analysed considering the overall classification accuracy. Results of the algorithm are satisfactory and acceptable in real time.