Moving Vehicle Detection and Recognition Technology based on Artificial Intelligence

The existing target detection and recognition technology has the problem of fuzzy features of moving vehicles, which leads to poor detection effect. A moving car detection and recognition technology based on artificial intelligence is designed. The point operation is adopted to enhance the high frequency information of the image, increase the image contrast, and delineate the video image tracking target. The motion vector similarity is used to predict the moving target area in the next frame of the image. The texture features of the moving car are extracted by artificial intelligence, and the center moment is calculated by the gray histogram distribution curve, the edge feature extraction algorithm is used to set the detection and recognition mode. Experimental results: under complex conditions, this design technology, compared with the other two kinds of moving vehicle detection and recognition technology, detected three more moving vehicles, which proved that the application prospect of the moving vehicle detection and recognition technology integrated with artificial intelligence is broader.

RFID Based Vehicle Toll Collection System for Toll Roads

The RFID-based vehicle collection program is intended to better handle toll operations through technology that aims to streamline the flow of vehicles. The purpose of this work is to plan, introduce and promote the automated operation of the car selection system (VTS). The Vehicle Toll Collection Device in this paper automatically detects vehicles and gathers machine-readable details on tolls for automobiles driving in the toll road. This knowledge is instigated by the modification and installation of at least one vehicle with a moving vehicle detection device. The computerized control device located along the toll line will transmit the registration signal as the car is reaching the registration point and will determine the toll to be debited and transfer the toll electronically to the account of the individual vehicle. This device helps a car to proceed beyond the scan point with no halting, thereby providing commuters with optimum comfort, speeding up traffic movement and reducing the need for human capital on highways

V-DaT: A Robust method for Vehicle Detection and Tracking

Vision-based traffic surveillance has been one of the most promising fields for improvement and research. Still, many challenging problems remain unsolved, such as addressing vehicle occlusions and reducing false detection. In this work, a method for vehicle detection and tracking is proposed. The proposed model considers background subtraction concept for moving vehicle detection but unlike conventional approaches, here numerous algorithmic optimization approaches have been applied such as multi-directional filtering and fusion based background subtraction, thresholding, directional filtering and morphological operations for moving vehicle detection. In addition, blob analysis and adaptive bounding box is used for Detection and Tracking. The Performance of Proposed work is measured on Standard Dataset and results are encouraging.