Excessive booming global population creates a widespread increase in traffic on Hi-tech modern roads. It is very much essential to detect vehicles and computing traffic congestion on highways. The key aspect is to hoard vehicle data through number plate detection. A deep learning model or Network has been developed to detect vehicles passes dynamically and efficiently. In the proposed work, a deep learning-based algorithm is proposed for detecting both vehicles and number plates for a reputed company surveillance dataset. The proposed model uses a video dataset as an input and the video has been segmented into several frames. Using pre-trained weights and labels of the dataset, the vehicles and its number plate are detected by the dark flow toolkit. This tool provides to extract the region of the vehicle with proper annotation. In future work, the proposed model aims to calculate the speed of the vehicle based on the surrounding area.
Tracing of Vehicle Region and Number Plate Detection using Deep Learning
2020-02-01
110956 byte
Conference paper
Electronic Resource
English
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