摘要: |
Law enforcement agencies throughout the nation are increasingly adopting automated license plate recognition (ALPR) technologies to enhance their enforcement and investigative capabilities, expand their collection of relevant data, and expedite the tedious and time consuming process of manually comparing vehicle license plates with lists of stolen, wanted, and other vehicles of interest. ALPR systems function to automatically capture an image of the vehicles license plate, transform that image into alphanumeric characters using optical character recognition or similar software, compare the plate number acquired to one or more databases of vehicles of interest to law enforcement and other agencies, and to alert the officer when a vehicle of interest has been observed. The automated capture, analysis, and comparison of vehicle license plates typically occurs within seconds, alerting the officer almost immediately when a wanted plate is observed. This National Institute of Justice (NIJ)-supported project was designed to assess and document ALPR implementation and operational experiences among law enforcement agencies in the United States, and to identify emerging implementation practices to provide operational and policy guidance to the field. Several data collection techniques were used to gather information for this project, including (1) a survey of law enforcement agencies to assess the scope of the current ALPR implementation, deployment, and operational uses, (2) site visits to interview law enforcement practitioners and observe ALPRs system in operation, and (3) reviewing documents and policies addressing ALPR implementation and use. |