Fare evasion violation processing method based on face recognition

Abstract

The invention provides a fare evasion violation processing method based on face recognition. Four databases are established, related information of a registered user, a temporary user and a code scanning in-out user, and related information of users with violation behaviors are stored respectively, the user travel is analyzed through travel matching and failure rules, automatic identification of the violation users is realized, and the code scanning users are screened out by comparing the code scanning in-out station library with the ticket-free in-out station users, so that the code scanningusers are prevented from being identified as fare evasion users; related information of users with violation behaviors is stored in an inspection library and issued to a fare evasion inspection terminal or a subway inspection large screen of a station worker of which each station in the whole network recognizes the face information of the user with violation behavior; therefore, real-time interception and violation processing of violation passengers are realized, the violation behaviors can be traced and checked by the user through a complete passenger violation record information evidence chain, and the violation cost is improved and the passengers are urged to take a bus and go out in a civilized manner through violation behavior display and honesty archive recording.

Description

technical field [0001] The invention relates to the field of face recognition detection, in particular to a method for processing fare evasion violations based on face recognition. Background technique [0002] The rapid development of the subway has given people convenient travel options, but the continuous opening and closing of the subway gates has added unnecessary congestion to peak travel, causing some people to take the opportunity to evade fares, and due to the congestion, the possibility of tracing is extremely low, so The cost of inspection is greater than the cost of violations. Even if the illegal passengers are traced, the amount of violations recovered is far less than the additional cost of tracing. In order to avoid more ticket damage, subway operators often manually review passengers in the form of spot checks Ticketing, in the morning and evening peak hours, has shortcomings such as low inspection efficiency, high difficulty, and easy interference with norm...

AI Technical Summary

Problems solved by technology

[0002] The rapid development of the subway has given people convenient travel options, but the continuous opening and closing of the subway gates has added unnecessary congestion to peak travel, causing some people to take the opportunity to evade fares, and due to the congestion, the possibility of tracing is extremely low, so The cost of inspection is greater than the cost of violations. Even if the illegal passengers are traced, the amount of violations recovered is far less than the additional cost of tracing. In order to avoid more ticket damage, subway operators often manually review passengers in the form of spot checks Ticketing, in the morning and evening peak hours, has shortcomings such as low inspection efficiency, high difficulty, and easy interference with normal passengers, and the focus of violations is mostly on fare evasion, buying short and long tickets, and unilateral tickets.

[0003] Passenger detection based on face recognition can distinguish passengers and be applied to individual face recognition and user payment to complete non-sense entry and exit and automatic deduction of face payment accounts. However, it lacks the application in fare evasion inspection and cannot It satisfies the automatic identification of violations such as fare evasion, buying short and long tickets, and unilateral fares, and does not reduce inspection costs and improve passenger awareness without meeting the traffic efficiency

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