EN-Feature Notes

AutoVu MLC

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How ALPR performance affects your operations © 2019 Genetec, Inc. All rights reserved. Genetec, the Genetec logo, Federation, Omnicast, Synergis, and AutoVu are either registered trademarks or trademarks of Genetec. All other trademarks contained herein are the property of their respective owners. AMLC_FN2EN How AutoVu MLC compares to traditional engines Genetec Inc. genetec.com/locations info@genetec.com @genetec Feature note · AutoVu MLC Rule-based engine AutoVu MLC Daily impact Capture rate 95.4% 98.6% +165 license plates captured Perfect read rate 91.5% 97.8% +368 license plate perfectly read Fuzzy Matchable Rate 97.3% 99.7% +244 matchable license plates False positives 1.6% 0.1% 50 fewer false alerts 1 Sample size: 1,511 license plates of various countries, including United States, Canada, Western Europe, etc. The Daily Impact column assumes an average of 3,500 reads per day. Capture rate The percentage of license plates that enter an ALPR camera's field of view and are read by the camera. The capture rate is the foundation of ALPR performance across all applications – detecting more license plates results in a higher chance to identify vehicles of interests or those not on a list of approved individuals. Misreads Misreads have different impacts depending on how ALPR is applied in operations. When ALPR is used to identify vehicles on a list, such as an offender or vehicle of interest list, misreads can let a target vehicle go by unnoticed. When used to identify employee or contractor vehicles, misreads can prevent a gate from opening and stalling customers requiring a human operator to intervene. Read rate The percentage of detected license plates that are read properly. A perfect read means that each individual character on the license plate was read properly. Other methods can be used to improve vehicle matching capabilities. The process of fuzzy matching replaces similar characters, such as 'B' or '8', in the matching engine and can require only a partial set of characters to be matched to a list before alerting operators. False positives When an ALPR camera identifies non-license plate text, such as lettering, roadside signage, or fences, and reads it as a license plate. This is especially problematic in applications where vehicles that are not present on a list generate an alert, such as permit enforcement. False positives interrupt the work of operators and require corrections to be entered in the system. They can also reduce the confidence of ALPR system users in the data gathered by their system, leading to slower response while they try to validate the read before taking action.

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