NIST Editor
NIST Editor and NIST viewer

There is the full description of product in the table below and a video demo of software execution are shown at the bottom of page.

Introducing the National Institute of Standards and Technology NIST

The ANSI / NIST-ITL standard data format is a standard format for storing and exchanging data in the form of fingerprints, faces and other biometric and image features, designed by NIST – National Standard of Standard and Technology Institute of the United States. This data format is used in AFIS fingerprint and face recognition systems for international exchange, and most biometric systems are capable of working with this data format.

ANSI / NIST-ITL data format

The textual information of the biometric features as well as their images are stored in WSQ compressed format in the form of a binary file in NIST format.

NIST Editor and NIST viewer

This software has the ability to create, view and edit data in NIST or the same format (ANSI / NIST) and can also be used for biometric systems.

The NIST Editor can read all the biometric components or features stored in this standard format and can display them in a structured way with the existing images. It is also possible to convert the data to other formats in the database according to your wishes. Because this data can not be searched or analyzed in binary format.

It is possible to customize biometric image data types with textual information in NIST format.

It is possible to save data with other image formats such as JPG, BMP, etc., as well as save features in a structured database and finally analyze the data statistically.

Software platform

The software is written in Java, but there is also the provision of communication with other programming languages.

The speed of data processing or creating a file with NIST Editor is less than one second, which of course depends on the amount and size and number of image data. It is possible to use the product to improve the efficiency of processing with this software that processed big data in the shortest possible time by multiprocessing and multithreading technique.

To save data with less size, you can also reduce the data volume by reducing the quality of image data in WSQ format.

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