Automated fingerprint identification refers to a procedure that evaluates an unidentified fingerprint with recognized fingerprints saved in the database. These systems are similar to access control systems and conventional attendance systems apart from that they provide real time identification of fingerprints.
Additionally, these systems facilitate variety of tasks such as editing, processing, retrieving, searching and saving fingerprint images. Moreover, law enforcement agencies use fingerprint identification systems for identification of criminals, person background check, authentication and fraud prevention measures.
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The global automated fingerprint identification has achieved a noteworthy attention attributed by increasing concern for security and unlawful activities. The need for effective investigation and trouble-free suspect identification has led to the increase in growth of automated fingerprint identification market.
Furthermore, the requirement for automation in storage of information and criminal identification system owing to slow conventional process of criminal identification has also resulted in increase in the market growth. Other factors impacting the market growth positively include developments in the digital technology and rising demand for fast process of fingerprint identification are projected to drive the market in the coming years.
However, accuracy and reliability of fingerprint identification are the key concerns associated in the criminal process. Technological failures related to deployment of hardware such as scanner, and faults in software algorithm for comparison of fingerprint are the main challenges hampering the market growth.
In addition, with the advancements in identification technologies such as facial recognition and palm recognition are anticipated to hinder the market growth for automated fingerprint identification. The increasing adoption of these systems by various private enterprises and government institutions in civil projects offers a potential opportunity to the automated fingerprint identification market.
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The Automated Fingerprint Identification Market is classified on the basis of components, applications, search type and geography. The component segment is analyzed into hardware and software.
The application segment is bifurcated into banking & finance, hospitality, transportation, government, healthcare and others. By search type, the market is segmented into ten-print to ten-print search and latent print to latent print search.
Geographically, the market is bifurcated into North America, Asia-Pacific, Europe, Middle East & Africa, and Latin America. The software segment, under component is leading the market of automated fingerprint identification and is anticipated to dominate the market in coming years.
Whereas, the transportation and government sectors plays a significant role in the market growth for automated fingerprint identification.
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North America is projected to hold the largest share and lead the market for automated fingerprint identification in the near future attributed by the presence of large number of biometric vendors and advancements in the technology. Asia-Pacific offers huge growth opportunities to the market owing to the increased adoption of automated fingerprint identification systems in the enterprises and by the law enforcement agencies.
Another factor influencing the growth in Asia-Pacific region is the increased concern for nation’s security. Also, the ten-print searches demand is anticipated to grow due to its extensive usage in sectors such as healthcare, hospitality and transportation, further leading to the growth of automated fingerprint identification market.
Some of the major players operating in the automated fingerprint identification market are 3M, Cogent Inc., NEC Corporation, Suprema Incorporation, HID Global Corporation, Dermalog Identification Systems GmbH, Papillon Systems, Afix Technologies Incorporation, Morpho SA, Fujitsu Limited, Crossmatch Technologies Inc., Sonda Technologies Ltd., M2SYS Technology and East Shore Technologies among others.
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