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Electronic Toll Collection Market Analysis

ID: MRFR//3536-CR | 128 Pages | Author: Ankit Gupta| October 2018

The burgeoning challenge of identifying vehicles amidst heavy traffic scenarios has prompted the integration of video surveillance coupled with analytics to discern vehicle owners. Video analytics has emerged as a highly effective tool, particularly in Automatic Number Plate Recognition (ANPR) systems, capable of scrutinizing vehicles on highways and expressways. In incidents such as road accidents, vehicle recognition plays a pivotal role in retracing the sequence of events. The ANPR system, in particular, is instrumental in detecting and identifying drivers who engage in overspeeding on highways or evade toll charges at toll facilities.

Furthermore, video analytics harnesses the concept of vehicle fingerprinting, constructing an image of the vehicle and cross-referencing it against a comprehensive database. However, challenges arise when dealing with clones or altered license plates, leading to potential inaccuracies in analytics outcomes. Complicating matters further is the diverse array of number plate formats adopted by different countries, necessitating advanced video analytics solutions capable of recognizing distinct patterns and printing styles associated with various number plate designs.

The escalating adoption of electronic toll collection systems has triggered a heightened demand for surveillance cameras equipped with higher resolution capabilities. This surge aims to capture high-quality images and videos essential for the implementation of advanced video analytics. The intersection of video surveillance and analytics not only aids in toll enforcement but also enhances overall road safety by facilitating the identification and tracking of vehicles involved in various incidents or infractions. As technology continues to evolve, the refinement of video analytics solutions is crucial for ensuring accuracy and reliability in the identification and management of vehicular activities on roadways.

Covered Aspects:

Report Attribute/Metric Details
Segment Outlook Technology, Means of Collection, and Application.
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