• KUCHINAD VAISHAK
• DR. H S JAYANNA

Machine learning is of great use in developing the tools that automatically detect and recognize the items in like cars, animals, humans etc. Recognizing the model of the vehicle is the sole aim of this paper. This paper represents an approach to recognize the model of a vehicle from CCTV footage from various angles. Vehicle model recognition system uses various methods with the quality of being new and original, where temporal processing is used to improve the reliability. The model of the vehicle is recognized from the frame of CCTV footage by any angle (front, back, side). Python programming is used for better understanding of logic and for ease of use in further design and implementation. This VMR design is divided into two phase where one phase deals with model detection of vehicle from side angles using machine learning algorithms based on design of vehicles, whereas the other phase deals with the model detection from front and back views of a vehicle which will detect the number plate and recognize the registration number of that vehicle which uses pattern recognition algorithms. The vehicle recognition can be done more accurately & with more accuracy nearly 100% when both phases are combined.

VMR, machine learning, pattern recognition.

"Vehicle Model Recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.441-444, May-2019, Available :http://www.jetir.org/papers/JETIR1905E64.pdf

"Vehicle Model Recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp441-444, May-2019, Available at : http://www.jetir.org/papers/JETIR1905E64.pdf