• Antony Allen Jabez.A
• Hariharasudhan.E
• Karthikeyan.J
• Gowthami.N

Due to recent improvements within increased utilization of vehicles and the highway research, there are more issues on vehicle management. Because of lack of security, plenty of vehicles are misplaced or stolen from various areas. To overcome this problem, a self-adaptive system has been designed to trace our required vehicle. The method of finding objects from a video plays a crucial part in video processing. The Optical Character Recognition may be a challenging process due to the difficulty in capturing the images with variations in shape of the object, multiple formats in the positions, differ in color, angle viewpoint and non-uniform illumination conditions at the time of image acquisition. The proposed model operates on two main stages namely objects detection, character recognition using the OCR model. Within the first stage, the article detection process takes place using Fritz AI with an end-to-end machine learning platform. Then, it captures the image and sends it to the database using the String-Request in Android Studio. Within the second stage, it collects the image from the database for the continuing process. Finally, the characters within the image get recognized with the assistance of OCR models and stored in the database. During this Database there are major security issues, and hence there is a must enhance the safety by providing an “Authentication and Authorization” mechanism to work out some specify the access levels to the user/client rights related to system resources in the database.

Optical Character Recognition, Object Detection, Vehicle management, Pattern Recognition, CNN

"OBJECT DETECTION USING OPTICAL CHARACTER RECOGNITION FOR VEHICLE MANAGEMENT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.14-18, April-2021, Available :http://www.jetir.org/papers/JETIRES06003.pdf

"OBJECT DETECTION USING OPTICAL CHARACTER RECOGNITION FOR VEHICLE MANAGEMENT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp14-18, April-2021, Available at : http://www.jetir.org/papers/JETIRES06003.pdf