Visual zone, MRZ, Barcode, RFID chip are parts of documents.
Visual Inspection Zone (VIZ)—the portions of the MRTD (data page in the case of MRP) designed for visual inspection, that is, front and back (where applicable), not defined as the MRZ.
Machine Readable Zone (MRZ)—the fixed dimensional area located on the MRTD, containing mandatory and optional data formatted for machine reading using OCR methods.
Barcode—the means of storing data as a pattern of lines or dots.
RFID chip—the radio frequency identification chip.
An MRZ (Machine Readable Zone) consists of 2 or 3 lines of encoded information, usually found on the lower part of an ID, where vital personal information about the document holder is encoded into a standardized format that can be quickly read and verified by a machine.
MRZ was introduced in the 1980s in order to speed up ID verification at borders and airports. Due to its accuracy and speed, other organizations and services soon adopted the technology. Today, machine-readable zones are included on a variety of documents, collectively referred to as Machine Readable Travel Documents (MRTD).
Barcodes are visual data, encoded into a machine-readable format. Invented in 1951, barcodes became popular when they began to be used for automated supermarket checkouts. Early barcodes (1D Barcodes) initially used vertical lines and spaces to encode numerical information, but due to their popularity and functionality, barcodes have since been developed and now employ a variety of machine-readable visual grids and matrices, containing many different types of information, such as price, personal data, ticket information.
Barcodes today are used in many different industries and can contain a wide variety of information. They are commonly used in retail for product identification, inventory, and pricing; in the Aviation industry for boarding passes and to track passenger bags; and in online marketing and advertising (known as QR Codes) to link consumers to data available on external sites.
OCR stands for Optical Character Recognition. It is the technology that converts typed, or printed text into machine data. Once converted, texts can then be electronically edited, searched, displayed, or stored. It is traditionally used for data entry and converting archival print documents (bank statements, insurance records, etc) for digital use.
Advanced OCRs utilize various pre-processing techniques to minimize errors and improve character recognition. Images captured by OCR can be de-skewed, de-speckled and normalized.
Regula goes beyond traditional OCR, providing advanced solutions for industry leaders. Our OCR uses pattern recognition, artificial intelligence and computer vision, expanding its capability and use. It is now a standard technology in a majority of industries.
Document Type Identification
Document Type Identification helps spot forged or invalid documents. This technology uses artificial intelligence and machine learning to identify which document is presented, check the legitimacy of a document by comparing it to a reference database of verified templates. Any document that does not have proper formatting,or layout can be singled out for inspection.
Document Type Identification can be performed on the document image from our extensive database. It is an easy and intuitive process. First, the user scans any document via their mobile or can be captured via the web. The scan is then assessed, the document type identified, and its key attributes are compared to corresponding template images. In all, the process is done in a matter of a second, on any ID document image submitted from any device, mobile or laptop, using Regula Document Reader SDK.
Face Matching is a technology that compares two facial portraits and analyses them for similarities. This involves a three step process. First is facial detection, where the software identifies a face in an image. The second step is the conversion of that facial image into digital information (the geometry of the face, spacing of the eyes, ears, nose, etc.). Finally, this information is compared to a second, reference photo and assessed for a match. There are 4 types of portraits that can be compared:
- Document printed portrait
- RFID chip DG2 portrait
- Portrait from an external camera (selfie from web or mobile device)
- An external portrait from database
The algorithms used are highly accurate— images are normalized to reduce lighting and motion effects, and normal physiological changes, such as a hair cut or glasses, are accounted for. Technology is used for security checks at airports and public events, to validate identity documents, to prevent identity theft, and stop the fraudulent use of credit cards and other documents.
Liveness Detection utilizes artificial intelligence and machine learning to examine and determine whether a live person is present and not a “spoof” or a fake. This helps improve systems that rely on biometrics, making them more resilient, accurate, and less vulnerable to deception.
Liveness detection can be performed using any 2D or 3D cameras. With the large-scale adoption of biometric security and identification technologies in recent years, liveness detection has become an increasingly important tool in combating fraud. Attacks directed against the biometric system, which are known as 'presentation attacks' become more common. Fraudsters obtain data via online fraud or through hacked security systems. Photos, videos played on tablets and even 3D masks have all been to counterfeit identity. Liveness detection is essential to combating these kinds of criminal acts.
RFID (Radio Frequency Identification) uses dedicated electromagnetic frequencies to transmit electronic information. An RFID tag stores and transmits data to a reader via an electromagnetic pulse. There are two types of RFID tags. Passive tags which rely on energy from the RFID reader for activation and; Active tags, which are battery powered and can be read at further distances.
Because RFID relies on electromagnetic waves, tags do not have to be visible to be read. This allows tags to be embedded into almost anything.
One of the most common uses for RFID technology is storing data on identity documents. This type of RFID application has become essential for industries like Aviation and Security, where documents such as Passports* or Biometric IDs are regularly fitted with RFID tags.