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In order to realize wide application of traditional image processing methods in intelligent transportation systems, the paper studied the identification and counting methods of vehicles in highway surveillance video. Using Python programming language and based on the OpenCV library, the design of the identification and counting function of vehicles was completed through a series of traditional image processing methods such as grayscale, denoising, background subtraction and morphological operations. This solution was compared with the solution based on the combination of the YOLOv3 model and the Simple Online and Realtime Tracking (SORT) algorithm. The results show that traditional image processing methods can detect moving target, but there are problems of low accuracy and low versatility compared with the solution based on deep learning. The paper therefore proposed the research suggestion of combining traditional image processing and deep learning.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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