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表紙：自動指紋識別システムの世界市場-2023年～2030年
市場調査レポート
商品コード
1352157

自動指紋識別システムの世界市場-2023年～2030年

Global Automated Fingerprint Identification Systems Market - 2023-2030

出版日
ページ情報
英文 202 Pages
納期
即日から翌営業日
カスタマイズ可能
適宜更新あり
価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=144.06円
自動指紋識別システムの世界市場-2023年～2030年
出版日: 2023年09月27日
発行: DataM Intelligence
ページ情報: 英文 202 Pages
納期: 即日から翌営業日
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概要

概要

世界の自動指紋識別システム市場は、2022年に85億米ドルに達し、2023-2030年の予測期間中にCAGR 23.2％で成長し、2030年には678億米ドルに達すると予測されています。

セキュリティ脅威の増大と信頼性の高い識別・認証方法へのニーズが、法執行、国境管理、アクセス管理など様々な分野での自動指紋識別システムの採用を促進しています。正確で高速な指紋照合アルゴリズムを含む指紋認識技術の進歩は、自動指紋識別システムシステムをより効率的で信頼性の高いものにしています。

指紋認証はバイオメトリクス認証方法として受け入れられつつあり、その採用はモバイル機器、金融取引、本人確認などの用途で拡大しています。世界中の多くの政府が、国家IDプログラム、パスポート管理、犯罪者識別データベースのために自動指紋識別システムを導入しており、自動指紋識別システム市場の成長に貢献しています。

2022年には、アジア太平洋地域が世界の自動指紋識別システム市場の約1/4を占め、最も急成長する地域となる見込みです。この地域の政府や組織は、法執行、国境管理、国民IDプログラム、入退室管理など、さまざまな目的でバイオメトリクス・ソリューションを採用する傾向が強まっています。

ダイナミクス

政府プロセスの増加

自動指紋識別システムは高レベルのセキュリティを提供し、指紋を通じて個人の身元を正確に確認します。犯罪現場で発見された指紋をデータベースと照合することで犯罪を解決し、複数の身元を持つ犯罪者を特定することにもつながります。

例えば、2023年8月12日、インドの国家犯罪記録局（NCRB）の全国自動指紋識別システム（NAFIS）チームは、行政改革・公的苦情処理省（DARPG）からデジタル変革カテゴリー1「政府プロセス・リエンジニアリングにおける優秀賞」の金賞を受賞した。

アミット・シャー内務大臣兼協力大臣は、NAFISチームのこの功績に祝辞を述べた。アミット・シャー氏は、ナレンドラ・モディ首相の安全なインドというビジョンに沿い、確実な指紋認証システムの構築に尽力するNAFISチームを称賛しました。

決済の安全性に対する懸念の増大

自動指紋認証システムは、指紋認証のようなバイオメトリクス認証方法を可能にすることで、決済セキュリティを強化するために使用されます。消費者は支払口座を指紋にリンクさせることで、不正ユーザーが金融情報にアクセスすることを極めて困難にしています。オンライン決済では、ユーザーは二要素認証プロセスで認証します。

例えば、2023年9月5日、ファーウェイ・モバイル・サービスは、アラブ首長国連邦の複数の大手銀行と戦略的パートナーシップを結び、同地域のデジタル・バンキングを強化しました。この提携には、ADCB、ENBD、FAB、Mashreq、ADIB、Standard Chartered Bank UAEなどの銀行が含まれ、これらのパートナーシップは、ファーウェイのユーザーに幅広い金融サービスを提供し、ファーウェイのAppGalleryで利用可能な銀行アプリを通じて口座にアクセスし、支払いを実行できるようにすることを目的としています。

技術進歩

生体認証技術の継続的な技術開拓には、市場の成長に重要な役割を果たした指紋認証が含まれます。指紋を通じて個人の身元を正確に確認することで高度なセキュリティを提供し、民間と公共の両セクターでセキュリティを強化する貴重なツールとなっています。また、迅速かつ正確な指紋照合も可能です。

例えば2023年6月6日、デバイス・インテリジェンス・プラットフォームであるフィンガープリントはフィンガープリント・プロ・プラスを発表しました。スマート・シグナルは、現在6,000社以上の企業が不正防止に使用しているフィンガープリントのブラウザーとデバイス識別シグナルを基に、リアルタイムで実用的なインテリジェンスを提供します。

この技術により、企業が使用するプラットフォームや意思決定エンジンは、ブラウザやモバイル・アプリケーション技術の変化に迅速に適応し、不正行為の特定精度を向上させることができます。

複雑な導入・維持プロセス

精度は指紋画像の品質と使用される照合アルゴリズムに依存します。質の悪い指紋やにじんだ指紋は、偽陰性や偽陽性を引き起こす可能性があります。AFISの有効性は指紋データベースのサイズと質に依存します。指紋がデータベースにない場合、この技術は人物を識別できません。巨大なデータベースを扱う場合、指紋照合には時間がかかります。リアルタイムの照合は常に実行可能とは限りません。

指紋データを保存することはプライバシーの問題を提起し、この機密情報がアクセスされたり、盗まれたり、悪用されたりする危険性があります。AFISシステムの導入および維持には費用がかかる場合があり、小規模組織や発展途上国では利用しにくくなります。環境条件は指紋画像の質に影響を与える可能性があります。指が濡れていたり、汚れていたり、損傷していたりすると、鮮明な指紋が得られないことがあります。

目次

第1章 調査手法と調査範囲

第2章 定義と概要

第3章 エグゼクティブサマリー

第4章 市場力学

  • 影響要因
    • 促進要因
      • 政府プロセスの増加
      • 決済の安全性に対する懸念の増大
      • 技術進歩
    • 抑制要因
      • 複雑な導入・維持プロセス
    • 機会
    • 影響分析

第5章 産業分析

  • ポーターのファイブフォース分析
  • サプライチェーン分析
  • 価格分析
  • 規制分析
  • ロシア・ウクライナ戦争の影響分析
  • DMIの見解

第6章 COVID-19分析

第7章 コンポーネント別

  • ソフトウェア
  • ハードウェア

第8章 検索タイプ別

  • テンプリント検索
  • 潜在検索

第9章 用途別

  • 管理
  • 政府機関
  • 銀行・金融
  • 医療
  • ホスピタリティ
  • その他

第10章 地域別

  • 北米
    • 米国
    • カナダ
    • メキシコ
  • 欧州
    • ドイツ
    • 英国
    • フランス
    • イタリア
    • ロシア
    • その他欧州
  • 南米
    • ブラジル
    • アルゼンチン
    • その他南米
  • アジア太平洋
    • 中国
    • インド
    • 日本
    • オーストラリア
    • その他アジア太平洋
  • 中東・アフリカ

第11章 競合情勢

  • 競合シナリオ
  • 市況/シェア分析
  • M&A分析

第12章 企業プロファイル

  • THALES
    • 企業概要
    • 製品ポートフォリオと説明
    • 財務概要
    • 主な動向
  • IDEMIA
  • SecuGen Corporation
  • Innovatrics
  • Aware Inc.
  • Suprema
  • Synaptics incorporated
  • DERMALOG Identification Systems GmbH
  • Precise biometrics
  • HID global Corporation

第13章 付録

目次
Product Code: ICT6916

Overview

Global Automated Fingerprint Identification Systems Market reached US$ 8.5 billion in 2022 and is expected to reach US$ 67.8 billion by 2030, growing with a CAGR of 23.2% during the forecast period 2023-2030.

Growing security threats and the need for reliable identification and authentication methods have driven the adoption of automated fingerprint identification systems in various sectors, that includes law enforcement, border control and access control. Advancements in technology in fingerprint recognition, which include accurate and faster fingerprint-matching algorithms, which have made automated fingerprint identification system systems more efficient and reliable.

Fingerprint recognition is a being accepted biometric authentication method and its adoption is growing in applications like mobile devices, financial transactions and identity verification. Many governments worldwide have implemented automated fingerprint identification systems for national ID programs, passport control and criminal identification databases, contributing to the growth of the automated fingerprint identification systems market.

In 2022, Asia-Pacific is expected to be the fastest growing region in the global automated fingerprint identification systems market having around 1/4th of the market. Governments and organizations across the region are increasingly adopting biometric solutions for various purposes, including law enforcement, border control, national ID programs and access control.

Dynamics

Rising Government Processes

Automated fingerprint identification systems provide a high level of security and accurately verify individual's identities through their fingerprints and this advancement is crucial for national security, border control and law enforcement. It helps law agencies to solve crimes by identifying fingerprints found in crime scenes with the database, which also leads to identifying criminals with multiple identities.

For instance, on 12 August 2023, The National Automated Fingerprint Identification System (NAFIS) team of the National Crime Records Bureau (NCRB) in India received the Gold Award under the Excellence in Government Process Reengineering for Digital Transformation Category-1 from the Department of Administrative Reforms and Public Grievances (DARPG).

Union Home Minister and Minister of Cooperation, Shri Amit Shah, congratulated the NAFIS team for this achievement. Shri Amit Shah commended the NAFIS team's dedication to creating a fool-proof fingerprint identification system, aligning with Prime Minister Shri Narendra Modi's vision of a secure India.

Growing Concerns for Payment Security

Automated fingerprint identification systems are used to enhance payment security by enabling biometric authentication methods like fingerprint recognition. Consumers link their payment accounts to their fingerprints which makes it extremely difficult for unauthorized users that access their financial information. Users authenticate with two factor authentication process for online payments.

For instance, on 5 September 2023, Huawei Mobile Services formed strategic partnerships with several leading banks in the United Arab Emirates to enhance the digital banking landscape in the region. The collaborations include banks such as ADCB, ENBD, FAB, Mashreq, ADIB and Standard Chartered Bank UAE and these partnerships aim to offer Huawei users a broader range of financial services, enabling them to access their accounts and conduct payments through banking apps available on the Huawei AppGallery.

Technology Advancement

The continuous development in technology of biometric technologies includes fingerprint recognition which has played a significant role in the growth of the market. It provides a high level of security by accurately verifying individual identities through fingerprints which makes valuable tools for enhancing security in both sectors, private and public. Also, it enables quick and accurate fingerprint matches.

For instance, on 6 June 2023, Fingerprint, a device intelligence platform, unveiled Fingerprint Pro Plus, which introduces Smart Signals, an innovation designed to enhance fraud prevention efforts. Smart Signals provides real-time, actionable intelligence that builds on Fingerprint's browser and device identification signals, currently used by over 6,000 companies for fraud prevention.

The technology enables platforms and decision engines used by companies to adapt quickly to changes in browser and mobile application technology, improving accuracy in identifying fraudulent activities.

Implementing and Maintaining is a Complex Process

The accuracy depends on the quality of the fingerprint images and the matching algorithms used. Poor-quality or smudged prints can result in false negatives or positives. The effectiveness of AFIS relies on the size and quality of the fingerprint database. The technology cannot identify a person if their fingerprints are not in the database. When dealing with a huge database, matching fingerprints can be time-consuming. Real-time matching may not always be feasible.

Storing fingerprint data raises privacy concerns and there is a risk that this sensitive information could be accessed, stolen or misused. Implementing and maintaining an AFIS system can be expensive, making it less accessible for smaller organizations or developing countries. Environmental conditions can affect the quality of fingerprint images. Wet, dirty or damaged fingers may not provide clear prints.

Segment Analysis

The global automated fingerprint identification systems market is segmented based component, search type, application and region.

Growing Adoption of Software in Automated Finger Identification Systems

Software component is expected to be the dominant segment with about 1/3rd of the market during the forecast period. The rise in crime rates, especially in urban areas, drives the demand for more efficient and accurate fingerprint identification systems. Law enforcement agencies require advanced AFIS software to solve crimes and identify suspects quickly.

According to the report by geeksforgeeks organization, more than 95% of the country's 16,098 police stations use the Crime and Criminal Tracking Network & Systems software and 97% have established connectivity. For instance, on 17 August 2022, The deployment of the National Automated Fingerprint Identification System (NAFIS) in India is a significant development in the country's law enforcement and criminal investigation efforts.

NAFIS is linked to the Crime and Criminal Tracking Network & Systems database and this integration ensures that every person arrested and recorded in CCTNS receives a unique identifier, which aids in tracking and identifying individuals involved in criminal activities.

Geographical Penetration

Rising Law Enforcement in North America

North America is among the growing regions in the global automated fingerprint identification systems market with round 1/3rd of the market in 2022. Owing to the rapid use in law enforcement and criminal justice systems, the region is the primary driver of the rise of automated fingerprint identification systems. Police departments, forensic labs and other organisations rely on automated fingerprint identification systems to identify criminals, solve crimes and manage crime databases.

For example, on March 9, 2023, IDEMIA, a global provider of secure identification solutions, expanded its partnership with Florida's Department of Law Enforcement to deliver a cloud-based Multi-Biometric Identification System. The solution is based on an automated biometric identification system that supports criminal investigators and law enforcement officers in assessing different biometric data types including fingerprints, palm prints and latent hand prints.

Competitive Landscape

The major global players in the market include: THALES, IDEMIA, SecuGen Corporation, Innovatrics, Aware Inc., Suprema, Synaptics incorporated, DERMALOG Identification Systems GmbH, Precise biometrics, HID global Corporation.

COVID-19 Impact Analysis

The pandemic disrupted the normal operations of law enforcement agencies and government offices, including those responsible for maintaining and operating automated fingerprint identification systems. Lockdowns, social distancing measures and reduced staffing affected the ability to process fingerprint data efficiently. The use of personal protective equipment (PPE), such as gloves, by law enforcement officers and fingerprint examiners became necessary during the pandemic.

Many government employees, including those working with automated fingerprint identification systems, had to adapt to remote work arrangements and this transition could have posed challenges in terms of accessing and managing fingerprint databases securely. The closure or limited operations of courts during the pandemic led to significant backlogs of criminal cases. As a result, fingerprint identification requests and caseloads for automated fingerprint identification systems operators may have increased.

Law enforcement agencies worldwide shifted their priorities during the pandemic to address public health and safety concerns related to COVID-19, this shift in focus may have affected the allocation of resources to AFIS-related projects and upgrades. The pandemic accelerated the adoption of touchless biometric authentication methods, such as facial recognition and iris scanning, in various applications and this could potentially impact the demand for traditional fingerprint-based systems.

AI Impact

AI has improved the accuracy of fingerprint-matching algorithms used in automated fingerprint identification systems. Machine learning and deep learning techniques have made it possible to identify matches even in cases with low-quality or partial fingerprint images. AI has accelerated the matching process in automated fingerprint identification systems, allowing for quicker identification of individuals and this is especially crucial in law enforcement and border control scenarios.

AI-powered automated fingerprint identification systems can handle larger databases of fingerprints efficiently, this scalability is vital as the volume of fingerprint data continues to grow. AI helps in reducing false positives and negatives, leading to more reliable results in identifying individuals and this is essential in criminal investigations and security applications.

For instance, on 31 August 2023, Google introduced an innovative watermarking solution to safeguard the authenticity of AI-generated images. The system integrates subtle watermarks into AI-generated images, serving as digital signatures to indicate that the images were created by artificial intelligence algorithms and this development is in response to concerns about the potential misuse and misrepresentation of AI-generated visuals, which have become increasingly difficult to distinguish from genuine photographs.

Russia- Ukraine War Impact

In regions affected by conflict, government agencies and law enforcement organizations may experience disruptions in their normal operations, including those related to automated fingerprint identification systems, this could lead to delays in fingerprint identification and criminal investigations. In times of conflict, there may be increased concerns about the security of sensitive biometric data stored in automated fingerprint identification systems databases.

During a war or conflict, government resources may be redirected toward immediate security and defense needs and this could affect the allocation of resources to maintain and upgrade systems. In cases where international collaboration on criminal investigations is necessary, geopolitical tensions resulting from the conflict could hinder cooperation between law enforcement agencies that rely on systems data sharing.

By Component

  • Software
  • Hardware

By Search Type

  • Tenprint Search
  • Latent Search

By Application

  • Commercial
  • Governments
  • Banking & Finance
  • Healthcare
  • Hospitality
  • Others

By Region

  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • France
    • Italy
    • Russia
    • Rest of Europe
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia-Pacific
    • China
    • India
    • Japan
    • Australia
    • Rest of Asia-Pacific
  • Middle East and Africa

Key Developments

  • On 15 May 2022, the Maharashtra government launched an Automated Multimodal Biometric Identification System aimed at improving crime detection and conviction rates and this advanced system stores fingerprints, palmprints, facial scans and eye scans of criminals and suspects digitally. It is designed to assist law enforcement agencies in identifying and tracking criminals using various biometric data, including palmprints and facial recognition.
  • On 22 January 2021, Fujitsu Laboratories introduced a multi-factor biometric authentication system aimed at facilitating contactless shopping in the post-COVID-19 era, this solution combines two forms of biometric authentication: facial verification, even when users are wearing masks and palm recognition.
  • On 5 June 2023, Pakistan's National Database Registration Authority (NADRA) introduced iris recognition technology in several cities to enhance the existing biometric verification system. Iris recognition is known for its high reliability and accuracy in identification. NADRA stated that this technology will complement the automated fingerprint identification system introduced over a decade ago and the facial recognition systems.

Why Purchase the Report?

  • To visualize the global automated fingerprint identification systems market segmentation based on component, search type, application and region, as well as understand key commercial assets and players.
  • Identify commercial opportunities by analyzing trends and co-development.
  • Excel data sheet with numerous data points of automated fingerprint identification systems market-level with all segments.
  • PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
  • Product mapping available as excel consisting of key products of all the major players.

The global automated fingerprint identification systems market report would provide approximately 61 tables, 58 figures and 202 pages.

Target Audience 2023

  • Manufacturers/ Buyers
  • Industry Investors/Investment Bankers
  • Research Professionals
  • Emerging Companies

Table of Contents

1. Methodology and Scope

  • 1.1. Research Methodology
  • 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

  • 3.1. Snippet by Component
  • 3.2. Snippet by Search Type
  • 3.3. Snippet by Application
  • 3.4. Snippet by Region

4. Dynamics

  • 4.1. Impacting Factors
    • 4.1.1. Drivers
      • 4.1.1.1. Rising Government Processes
      • 4.1.1.2. Growing Concerns for Payment Security
      • 4.1.1.3. Technology Advancement
    • 4.1.2. Restraints
      • 4.1.2.1. Implementing and Maintaining is a Complex Process
    • 4.1.3. Opportunity
    • 4.1.4. Impact Analysis

5. Industry Analysis

  • 5.1. Porter's Five Force Analysis
  • 5.2. Supply Chain Analysis
  • 5.3. Pricing Analysis
  • 5.4. Regulatory Analysis
  • 5.5. Russia-Ukraine War Impact Analysis
  • 5.6. DMI Opinion

6. COVID-19 Analysis

  • 6.1. Analysis of COVID-19
    • 6.1.1. Scenario Before COVID
    • 6.1.2. Scenario During COVID
    • 6.1.3. Scenario Post COVID
  • 6.2. Pricing Dynamics Amid COVID-19
  • 6.3. Demand-Supply Spectrum
  • 6.4. Government Initiatives Related to the Market During Pandemic
  • 6.5. Manufacturers Strategic Initiatives
  • 6.6. Conclusion

7. By Component

  • 7.1. Introduction
    • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 7.1.2. Market Attractiveness Index, By Component
  • 7.2. Software*
    • 7.2.1. Introduction
    • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 7.3. Hardware

8. By Search Type

  • 8.1. Introduction
    • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Search Type
    • 8.1.2. Market Attractiveness Index, By Search Type
  • 8.2. Tenprint Search*
    • 8.2.1. Introduction
    • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 8.3. Latent Search

9. By Application

  • 9.1. Introduction
    • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 9.1.2. Market Attractiveness Index, By Application
  • 9.2. Managed*
    • 9.2.1. Introduction
    • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 9.3. Governments
  • 9.4. Banking & Finance
  • 9.5. Healthcare
  • 9.6. Hospitality
  • 9.7. Others

10. By Region

  • 10.1. Introduction
    • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
    • 10.1.2. Market Attractiveness Index, By Region
  • 10.2. North America
    • 10.2.1. Introduction
    • 10.2.2. Key Region-Specific Dynamics
    • 10.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 10.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Search Type
    • 10.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 10.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 10.2.6.1. U.S.
      • 10.2.6.2. Canada
      • 10.2.6.3. Mexico
  • 10.3. Europe
    • 10.3.1. Introduction
    • 10.3.2. Key Region-Specific Dynamics
    • 10.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 10.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Search Type
    • 10.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 10.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 10.3.6.1. Germany
      • 10.3.6.2. UK
      • 10.3.6.3. France
      • 10.3.6.4. Italy
      • 10.3.6.5. Russia
      • 10.3.6.6. Rest of Europe
  • 10.4. South America
    • 10.4.1. Introduction
    • 10.4.2. Key Region-Specific Dynamics
    • 10.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 10.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Search Type
    • 10.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 10.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 10.4.6.1. Brazil
      • 10.4.6.2. Argentina
      • 10.4.6.3. Rest of South America
  • 10.5. Asia-Pacific
    • 10.5.1. Introduction
    • 10.5.2. Key Region-Specific Dynamics
    • 10.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 10.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Search Type
    • 10.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 10.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 10.5.6.1. China
      • 10.5.6.2. India
      • 10.5.6.3. Japan
      • 10.5.6.4. Australia
      • 10.5.6.5. Rest of Asia-Pacific
  • 10.6. Middle East and Africa
    • 10.6.1. Introduction
    • 10.6.2. Key Region-Specific Dynamics
    • 10.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 10.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Search Type
    • 10.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application

11. Competitive Landscape

  • 11.1. Competitive Scenario
  • 11.2. Market Positioning/Share Analysis
  • 11.3. Mergers and Acquisitions Analysis

12. Company Profiles

  • 12.1. THALES*
    • 12.1.1. Company Overview
    • 12.1.2. Product Portfolio and Description
    • 12.1.3. Financial Overview
    • 12.1.4. Key Developments
  • 12.2. IDEMIA
  • 12.3. SecuGen Corporation
  • 12.4. Innovatrics
  • 12.5. Aware Inc.
  • 12.6. Suprema
  • 12.7. Synaptics incorporated
  • 12.8. DERMALOG Identification Systems GmbH
  • 12.9. Precise biometrics
  • 12.10. HID global Corporation

LIST NOT EXHAUSTIVE

13. Appendix

  • 13.1. About Us and Services
  • 13.2. Contact Us