Salvato in:
| Autore principale: | |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2022
|
| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2210.06586 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866916958412210176 |
|---|---|
| author | Orun, Ahmet |
| author_facet | Orun, Ahmet |
| contents | Selection of appropriate template matching algorithms to run effectively on real-time low-cost systems is always major issue. This is due to unpredictable changes in image scene which often necessitate more sophisticated real-time algorithms to retain image consistency. Inefficiency of low cost auxiliary hardware and time limitations are the major constraints in using these sorts of algorithms. The real-time system introduced here copes with these problems utilising a fast running template matching algorithm, which makes use of best colour band selection. The system uses fast running real-time algorithms to achieve template matching and vehicle classification at about 4 frames /sec. on low-cost hardware. The colour image sequences have been taken by a fixed CCTV camera overlooking a busy multi-lane road |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2210_06586 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Automatic Real-time Vehicle Classification by Image Colour Component Based Template Matching Orun, Ahmet Computer Vision and Pattern Recognition Artificial Intelligence Selection of appropriate template matching algorithms to run effectively on real-time low-cost systems is always major issue. This is due to unpredictable changes in image scene which often necessitate more sophisticated real-time algorithms to retain image consistency. Inefficiency of low cost auxiliary hardware and time limitations are the major constraints in using these sorts of algorithms. The real-time system introduced here copes with these problems utilising a fast running template matching algorithm, which makes use of best colour band selection. The system uses fast running real-time algorithms to achieve template matching and vehicle classification at about 4 frames /sec. on low-cost hardware. The colour image sequences have been taken by a fixed CCTV camera overlooking a busy multi-lane road |
| title | Automatic Real-time Vehicle Classification by Image Colour Component Based Template Matching |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2210.06586 |