Automatic number-plate recognition is a technology that uses optical character recognition on images to read vehicle registration plates to create vehicle location data. It can use existing closed-circuit television, road-rule enforcement cameras, or cameras specifically designed for the task. ANPR is used by police forces around the world for law enforcement purposes, including to check if a vehicle is registered or licensed. It is also used for electronic toll collection on pay-per-use roads and as a method of cataloguing the movements of traffic, for example by highways agencies.
Scope of the Report:
the global automatic number plate recognitionmarket is valued at 540 million usd in 2017 and is expected to reach 1180 million usd by the end of 2023, growing at a cagr of 14.1% between 2017 and 2023.
The Asia-Pacific will occupy for more market share in following years, especially in China, also fast growing India and Southeast Asia regions. North America, especially The United States, will still play an important role which cannot be ignored. Any changes from United States might affect the development trend of Automatic Number Plate Recognition. Europe also play important roles in global market, with market size of xx million USD in 2017 and will be xx million USD in 2023, with a CAGR of xx%.
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Market Segment by Companies, this report covers
- 3M Company
- Siemens AG
- Intelligent Traffic Solutions Ltd.
- Genetec Inc.
- Vigilant Solutions Inc.
- Bosch Security Systems
- CA Traffic Limited
- ELSAG North America
- COBAN Technologies
- NDI Recognition Systems
Market Segment by Regions, regional analysis covers
- North America (United States, Canada and Mexico)
- Europe (Germany, France, UK, Russia and Italy)
- Asia-Pacific (China, Japan, Korea, India and Southeast Asia)
- South America (Brazil, Argentina, Colombia)
- Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)
Market Segment by Type, covers
- Security & Surveillance
- Vehicle Parking
- Traffic Management
- Toll Enforcement
Market Segment by Applications, can be divided into
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