Document recognition system of text-to-pass iOS platform

Source: Internet
Author: User

Keywords

iOS platform, identity card identification, driver license identification, driving license identification, vehicle VIN code identification, passport recognition, military ID identification, business card identification, second-generation identification.


Product Description

Wen Tong Document recognition system is a mobile platform-based document recognition application developed by Beijing Wen Tong Technology Co., Ltd., which supports many mainstream mobile operating systems such as Android and iOS. This product uses the mobile phone, the tablet computer camera to take the document image, then through the OCR software to identify the document information to extract.


Featured Features

    • Support 180-degree, 90-degree automatic rotation function;
    • Supporting complex backgrounds (such as holding documents in the hands) and trimming them;
    • Support automatic tilt correction function, improve the recognition rate;
    • The recognition result is processed, the recognition result is added to the rule, and the recognition rate is improved.

Function Introduction

    • Through the photo screen, the user is instructed to take a qualified document image.
    • Use Word recognition (OCR) technology to automatically extract document information (such as name, ID number, address, etc.) and Avatar.
    • Identification of the types of documents including, identity cards, driving licences, passports, Hong Kong, Macao and Taiwan documents, military certificates, business cards and other identity documents, as well as driving permits, vehicle VIN code and other vehicle information.
    • According to user requirements can be customized to develop other types of license (such as business licenses, invoices, cheques, etc.).
    • Provides an iOS platform. A static library development kit.

Configuration requirements

    • Operating system: Support iOS6.0 or above
    • Camera: Auto focus support, macro shooting support
    • Setup takes up space, 8MBytes

Shooting specifications

    • Standard shooting helps to improve recognition rate
    • Light, attention to the impact of light, as far as possible to avoid reflection and shadow;
    • Angle, do not tilt the shooting angle too large, so as not to cause serious image distortion;
    • Background, less background (that is, documents filled with pictures) or simple background, can improve the recognition rate;
    • Focus, focus on clarity, avoid unclear text ambiguity.

Authorization method

    • Serial number authorization mode, authorized by the number of smart Terminal clients (License)
      --Automatic activation (mobile Internet)
      --Manual activation (mobile offline)
    • Time authorization, version authorization

Typical applications

    • Insurance: Motor Vehicle Motion Survey, information acquisition and driver identification information
      Life Insurance Mobile exhibition industry, collect ID card, business card, bank card number
    • Real-name telecommunications: Agent network to collect identity card information
    • Credit Card application: Collect ID card and business card information
    • Securities Mobile Account: Collect ID card, bank card number
    • Network real-Name authentication: Collect identity card information
    • Police: Patrol duty, mobile law enforcement, traffic Police law enforcement (ID card, driver's license, driving license, car grade identification)
    • Comprehensive administrative enforcement of urban management: Identification of identity card, driver's license
    • Rental house Travel (small hotel) management: Check-in guest registration
    • Floating population management: household survey
    • Community-based grid management: collecting Document Information
    • Used Car transactions: acquisition of identity cards, driving permits


Free Download Experience

You can download the installation by searching for "document identification" in the Apple App Store.

Document recognition system of text-to-pass iOS platform

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