Automated Fingerprint Identification Market Projected to Garner Significant Revenues by 2023
Posted: Feb 16, 2019
Automated fingerprint identification is a procedure which looks at an unidentified finger impression against perceived fingerprints put away in a database. These frameworks are identified with regular participation and get to control frameworks aside from that they present real finger impression distinguishing proof. Moreover, these systems permit extensive variety of assignments, for instance, handling, altering, looking, recovering, and putting away of fingerprint pictures. Automated fingerprint identification systems are frequently utilized by law implementation offices for criminal distinguishing proof, validation, individual historical verification, and as a measure against fraud prevention. Moreover, currently automated identification systems are utilized by government, and private ventures for security and recognizable proof reason. These frameworks are utilized as a part of different applications, such as public safety, e passports, national identity cards, latent print machine, voter registration, and border control.
Automated fingerprint identification has increased huge consideration over the globe owing to the rising concerns related to security and unlawful exercises. The need for viable examination and simple suspect identification has expanded the ease to tackle crimes. Likewise, the automation in criminal identification systems and storage of data is expanding because of drowsy traditional criminal identification proof process. Moreover, the progressions in advanced hardware innovation and expanding demand for fast fingerprint identification are relied upon to drive the Market For Automated Fingerprint Identification. In any case, the dependability and precision of fingerprint identification is a worry in the process of criminal identification.
Automated fingerprint identification is a process which compares an unidentified fingerprint against recognized fingerprints stored in a database. These systems are related to conventional attendance and access control systems except that they offer real time fingerprint identification. In addition, these systems allow wide range of tasks such as processing, editing, searching, retrieving, and storing of fingerprint images. Automated fingerprint identification systems are often used by law enforcement agencies for criminal identification, authentication, person background check, and fraud prevention measure. Furthermore, at present automated identification systems are used by government, and private enterprises for security and identification purpose. These systems are used in various applications such as border control, voter registration, latent print matching, national identity cards, e passports, and public safety.
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Automated fingerprint identification has gained significant attention across the globe, due to rising security concerns and unlawful activities. The necessity for effective investigation and easy suspect identification has increased to solve crime. In addition, the demand for automation in criminal identification system and storage of information is increasing due to sluggish conventional criminal identification process. Furthermore, the advancements in digital electronics technology, and increasing demand for faster fingerprint identification are expected to drive the automated fingerprint identification market. However, the reliability, and accuracy of fingerprint identification is a major concern in the criminal identification process.
In addition, technical failures in the integration of hardware such as fingerprint scanner, and defects in software algorithm for fingerprint comparison are the key challenges restraining this market. Furthermore, with increasing development in identification technologies such as palm recognition, and facial recognition are expected to restraint the adoption of automated fingerprint identification market. The rising adoption of automated fingerprint identification by government, and private enterprises in civil identification projects provide opportunity for automated fingerprint identification market. Further, developments in cloud based automated fingerprint identification systems offer additional growth opportunities. For instance, the M2SYS Technology has introduced cloud based identification system to increase the scalability, and reduce hardware cost related to automated fingerprint identification systems.
Automated fingerprint identification (AFI) market is segmented by component, platform, search type, application, and geography. By component, AFI market is segmented into sensors, microprocessors/ microcontrollers, and others. Sensors are further segmented into optical, capacitive, pressure based, and ultrasound. Based on platform, the AFI market is segmented into on-premise, and cloud based. By search type, the AFI market is segmented into tenprint to tenprint, latent print to latent print, and others (tenprint to latent print viz.). By application, the AFI market is segmented into government, banking and finance, healthcare, enterprise, and others. On the basis of geography, the AFI market is segmented into North America, Europe, Asia Pacific, Latin America, and Middle East and Africa. Among these regions, North America and Europe have witnessed large scale adoption of automated fingerprint identification systems due to increasing security measures, and technological advancements in security systems. In the U.S., these systems are widely used, and managed by the Federal Bureau of Investigation (FBI) for criminal identification. Asia Pacific, and Middle East and Africa are expected to see healthy growth in the AFI market due to increasing demand for identification systems in automation.
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The rapid development in digital electronics technology, and software systems has compelled many companies to introduce improved automated fingerprint identification systems. The key companies operating in this market include Fujitsu Limited, Suprema, Inc., 3M Cogent, Inc., Papillon Systems, M2SYS Technology, NEC Corporation, Morpho Detection LLC, Cross Match Holdings, Inc., 4G Identity Solutions Pvt. Ltd., Identification International, Inc., Sonda Technologies, Biometrics4All, Inc., HID Global Corporation/ASSA ABLOY AB., AFIX Technologies, Inc., and MOSA Technology Solutions, Inc.
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