# MegaMatcher ABIS Online --- ## Pages - [Thank you](https://www.megamatcher.online/thank-you/) - [MegaMatcher ABIS 30-day trial](https://www.megamatcher.online/megamatcher-abis-30-day-trial/) - [News](https://www.megamatcher.online/news/) - [Voter Registration](https://www.megamatcher.online/solutions/voter-registration/): To make voting process fair and legal, voters can be identified with their biometric data that none of the electors voted more than once. - [Homeland Security](https://www.megamatcher.online/solutions/homeland-security/): It helps not only to check if the person is wanted, but also controls if the identity document belongs to the particular person and is not stolen. - [Law Enforcement](https://www.megamatcher.online/solutions/law-enforcement/): Find the criminal by using his biometrical data is quite standard and effective scenario for police or other law enforcement institutions. - [Social Services](https://www.megamatcher.online/solutions/social-services/): Projects where biometrical data is used to identify person, who doesn’t have any personal identification document. For example food sharing, charity, etc. - [Commercial Applications](https://www.megamatcher.online/solutions/commercial-applications/): Fingerprint, iris and facial recognition technologies become more mainstream in banking and financial services. - [Civil Identification](https://www.megamatcher.online/solutions/civil-identification/): Large scale projects, where high accuracy and speed is important. MMABIS makes biometric passports or identity cards projects easily implementable. - [Home](https://www.megamatcher.online/): MegaMatcher ABIS is a complete and ready-to-use solution based on award winning fingerprint, face and iris recognition technologies. - [Privacy Policy](https://www.megamatcher.online/privacy-policy/): In this Privacy Policy we describe how information from User (User) is collected, used, maintained and disclosed by MegaMatcher. - [Pricing](https://www.megamatcher.online/pricing/): Check MegaMatcher ABIS API subscription pricing plans. For even bigger projects please contact us directly to receive an offer. - [About company](https://www.megamatcher.online/about-company/): Neurotechnology was founded with the idea of using neural networks for applications such as biometric person identification, computer vision, robotics & A.I - [Contacts](https://www.megamatcher.online/contacts/): +370 5 277 3315 | Laisves av. 125A, Vilnius, LT-06118, Lithuania | support@megamatcher.online - [Solutions](https://www.megamatcher.online/solutions/): MegaMatcher could be used for national ID, voter registration, border control, social services, banking systems, government e-services. --- ## Posts - [Ghana Elections Voter Management System - press release](https://www.megamatcher.online/case-studies/ghana-elections-voter-management-system/) - [India's Aadhaar ID program - press release](https://www.megamatcher.online/case-studies/india-aadhaar-id-program-press-release/) - [Limitless opportunities for Biometric technologies](https://www.megamatcher.online/articles/limitless-opportunities-for-biometrics-technologies/): Accurately identifying individuals is the first step towards a more secure society. In such a digital age security continues being... - [MINEX III Compliance](https://www.megamatcher.online/awards/minex-iii-compliance/): The MINEX III evaluation is a NIST SP 800-76-2 Biometric Specifications for Personal Identity Verification U.S. Government program compliance evaluation. - [FVC-onGoing results](https://www.megamatcher.online/awards/fvc-ongoing-results/): In 2019 MegaMatcher SDK palm print matching algorithm has shown the top result at the FVC-onGoing evaluation. - [Ukraine's National Biometric Verification and Identification System](https://www.megamatcher.online/case-studies/national-biometric-verification-and-identification-system-of-ukraine/) - [IREX IX Results](https://www.megamatcher.online/awards/irex-ix-results/): Neurotechnology’s iris recognition algorithms have been judged by NIST as the second most accurate among the IREX IX participants. - [DR Congo Voter Registration Project - Case Study](https://www.megamatcher.online/case-studies/dr-congo-voter-registration-project/): For the DRC, more than 46.5 million voter records were collected with 10 fingerprints and a facial biometric for each record. - [FRVT Ongoing](https://www.megamatcher.online/awards/frvt-ongoing/): Neurotechnology has been ranked among 8 most accurate face recognition algorithm vendors out of 39, with tenth most accurate algorithm out of 78. - [PFT II (Proprietary Fingerprint Template) Evaluation](https://www.megamatcher.online/awards/pft-ii-proprietary-fingerprint-template-evaluation/): In 2017 Neurotechnology fingerprint algorithm was submitted to NIST Proprietary Fingerprint Template Evaluation II. Accuracy was among the best. - [Somaliland National ID Project](https://www.megamatcher.online/case-studies/somaliland-national-id-project/): Somaliland government decided to register all Somaliland citizens for the creation of a biometric National Identity Card system. - [Sri Lanka Foreign Employment Passport Tracking & AFIS System](https://www.megamatcher.online/case-studies/sri-lanka-foreign-employment-passport-tracking-afis-system/): The Sri Lanka Bureau of Foreign Employment needed a way to accurately identify and record Sri Lankan citizens working in countries around the world. - [Venezuela’s New Biometric Voter Registration System](https://www.megamatcher.online/case-studies/venezuelas-new-biometric-voter-registration-system/): The National Electoral Council of Venezuela wanted to update their existing voter registration system with a more open and cost-effective technology. - [Indian States Criminal AFIS](https://www.megamatcher.online/case-studies/indian-states-criminal-afis/): Indian police departments required a tool for the investigation of criminal activity through the quick and accurate identification. - [FpVTE 2012](https://www.megamatcher.online/awards/fpvte-2012/): The evaluation used operational fingerprints datasets which contained several million subjects and tested one-to-many identification scenarios. - [Bosnia and Herzegovina Biometric Passport and ID System](https://www.megamatcher.online/case-studies/bosnia-and-herzegovina-biometric-passport-and-id-system/): The system, which was launched in October 2009, uses MegaMatcher components and ensures quality and accuracy required to meet European Union standards. - [Border control systems in Spanish airports](https://www.megamatcher.online/case-studies/border-control-systems-in-spanish-airports/): The systems perform a dual biometric test using facial and fingerprint recognition for passenger identity verification. - [Poland Biometric Passport System](https://www.megamatcher.online/case-studies/poland-biometric-passport-system/): Polish Security Printing Works, working closely with the Polish government selected Neurotechnology’s VeriFinger fingerprint recognition technology. --- # # Detailed Content ## Pages What is voter registration and why does it matter? Voter registration is the key process that establishes which individuals are eligible to vote. The voter registration process varies widely across countries. In some countries, voters are automatically registered when they turn of voting age or when they move to a new place of residence. In other countries, the voter has to take specific steps to register. In all voter registration processes, the government must provide eligible voters with fair access to the process. The voter registration process has three goals: Voter registration makes sure eligible citizens have a real opportunity to vote;Voter registration prevents ineligible people from voting; andVoter registration should prevent multiple voting. Using Biometrics for Voter Registration  Voter registration remains one of the most complex and contested parts of the electoral process. In countries where there is no trustworthy population census and no reliable identification documents, voter registration is even more complicated. Existing registers are often of poor quality, thus opening up avenues for manipulation and putting pressure on electoral management bodies to establish more reliable registration systems. In such a situation, it is often assumed that biometric technology can provide the required solutions. Although the procedures and modalities engaged may differ, biometric recognition needs to undergo the same three stages of voter enrolment, exception handling and voter verification. Voter Enrollment Prior to using a biometric system, the voter should be enrolled. A scanner is usually needed to convert some piece of biometric information (e. g. , a... --- Using Biometrics to Keep Your Borders Secure For the authorities safeguarding national borders, Neurotechnology offers a robust and convenient to use automated biometric identification system (ABIS). You can streamline your immigration procedures by adopting our multimodal ABIS for your border control system. Due to agile integration of fingerprint, face, iris and palmprint recognition technologies, crossing the border checkpoints will bring delight to the travelers and reduce stress for the homeland officers even at the peak traffic hours. Flexible Choice of Biometric Modalities We are dedicated to consistent improvement of all our algorithms to make them even faster and more accurate. The architecture of our ABIS supports easy scaling and integration. --- With our Criminal Identification solution, the law enforcement community is provided with a handy platform for using our proprietary biometric technologies to identify suspects fast and accurately. AI-based Criminal Identification Solution from Neurotechnology Neurotechnology ABIS integrates fingerprint, face and palmprint recognition technologies in a powerful software package that streamlines the investigation process by enabling rapid queries in huge databases with millions of records. For many years, we are the front-runners at the NIST algorithmic challenge for the best fingerprint recognition within the categories of both speed and accuracyOur algorithm for iris recognition was judged by NIST as the second most accurate in 2020Our algorithm for matching palm prints has been the most accurate overall and fastest among the five most accurate candidates as evaluated by NIST in 2019Our algorithm for face recognition was among the top most accurate in the vendor competition of 2018The architecture of our ABIS supports easy scaling and integration --- Better Efficiency through Biometric Solutions Running public social services nowadays such as a national healthcare program, a pension system, or a refugee management system is a complex process. Streamlining administration of this process calls for a dependable, flexible and effective IT system. Neurotechnology invites you to modernize the management of your social services by introducing our multibiometric solutions. By connecting an Automated Biometric Identification System (ABIS) with multiple physical locations, storing and matching of biometric data can be done centrally. With the facilitated person identification and authentication process, you can expect unprecedented gains in the quality of your social services. High-Performance Algorithms For many years, the fingerprint, iris and face recognition algorithms by Neurotechnology are among the best in the world based on the annual evaluations by NISTWe are dedicated to consistent improvement of all our algorithms to make them even faster and more accurate. --- Reliable Identity Check through Biometric Authentication At Neurotechnology, we have developed innovative solutions for providing financial institutions with alternative biometrics-based identification of their customers. This way, conventional entering of PIN codes or logins can be conveniently replaced by, for example, a simple smartphone selfie supported by trusted identity check through verification of biometrics. High-Performance Algorithms For many years, the fingerprint, iris and face recognition algorithms by Neurotechnology are among the best in the world based on the annual evaluations by NISTWe are dedicated to consistent improvement of all our algorithms to make them even faster and more accurate --- Improved Service for Everyone through Verified Biometric Identity The civil identification solutions by Neurotechnology take advantage of the state-of-the-art biometric techniques for counterfeit-proof identification of persons along with reliable verification of this identity. Safeguard Identity by Precluding Deception As counterfeiting the identity of an individual could be a straightforward matter when using the conventional means, Neurotechnology offers its biometric approach to the problem of flawless civil identification that is based on fingerprint, palmprint, face and iris recognition. AI-based Biometric Identification Solution from Neurotechnology Our solution offers foolproof security for civil identity documents such as passports, national ID cards, drivers licenses, health insurance cards, etc. Actually, the solution will support identifying individuals based solely on their fingerprints and/or face even when no ID is available. For many years, we are the front-runners at the NIST algorithmic challenge for the best fingerprint recognition within the categories of both speed and accuracyOur algorithm for iris recognition was judged by NIST as the second most accurate in 2020Our algorithm for matching palm prints has been the most accurate overall and fastest among the five most accurate candidates as evaluated by NIST in 2019Our algorithm for face recognition was among the top most accurate in the vendor competition of 2018The architecture of our ABIS supports easy scaling and integration --- MMABIS solution provides Web Client which enables subjects’ enrollment, identification, verification and duplicate check. These operations are performed by MMABIS operator. This privacy policy applies to the megamatcher. online website (“Site”) and all products and services offered by MegaMatcher. Collection of personal information We may collect personally-identifying information, including the IP address and other internet server provider related information, when User: Visits the Site. Registers on the Site. Fills a form. Subscribes for a newsletter. Makes other activities connected to the Site features and services. We may ask User for: Name and / or Company name. Email. Website address. Phone/Fax Address Other. User may visit the Site anonymously and refuse to provide personal information when asked, however, this may prevent User from using certain Site features and services. While User accesses the Site we may collect certain non-personally-identifying information: Browser type. Operation system. Region of the world. Other similar information. We may use “cookies” – special files which browser may store on Users computer to retain certain information from visit to visit to the Site to enhance the Site user experience. User may switch off using of the “cookies” in Users browser; however, some parts of the Site may not function properly. We will not collect any other personal data about you from other sources. In case you think we may have more personal data of you than you provided, you may contact our support team support@megamatcher. online with request to provide you with all personal data about you we... --- 500€/ month Maximum capacity 500,000 records Enrollment operations 50,000 per month 2,500 per day 500 per hour Identification operations 50,000 per month 2,500 per day 500 per hour Users Included users 1 Additional user starting from 5€ 30 DAYS TRIAL 1,000€/ month Maximum capacity 1,500,000 records Enrollment operations 125,000 per month 7,500 per day 1,500 per hour Identification operations 125,000 per month 7,500 per day 1,500 per hour Users Included users 2 Additional user starting from 5€ ORDER 2,000€/ month Maximum capacity 2,500,000 records Enrollment operations 250,000 per month 20,000 per day 5,000 per hour Identification operations 250,000 per month 20,000 per day 5,000 per hour Users Included users 3 Additional user starting from 5€ ORDER 5,000€/ month Maximum capacity 10,000,000 records Enrollment operations 750,000 per month 50,000 per day 10,000 per hour Identification operations 750,000 per month 50,000 per day 10,000 per hour Users Included users 5 Additional user starting from 5€ ORDER 10,000€/ month Maximum capacity 25,000,000 records Enrollment operations 1,500,000 per month 75,000 per day 15,000 per hour Identification operations 1,500,000 per month 75,000 per day 15,000 per hour Users Included users 10 Additional user starting from 5€ ORDER 0EUmonth Maximum capacity Enrollment operations Per month Per day Per hour Identification operations Per month Per day Per hour Users Included users Additional users 30 DAYS TRIAL 500€/ month 500,000 records 50,000 2,500 500 50,000 2,500 500 1 Starting from 5€ 30 DAYS TRIAL 1,000€/ month 1,500,000 records 125,000 7,500 1,500 125,000 7,500 1,500 2 Starting from 5€... --- Neurotechnology Neurotechnology was founded in Vilnius, Lithuania in 1990 with the key idea of using neural networks for applications such as biometric person identification, computer vision, robotics and artificial intelligence. Much to our delight, we were able to endure the "neural networks winter" by using and expanding this expertise all through 2012, the year that brought explosive developments in the concept and infrastructure of deep neural networks. This allowed us to quickly take advantage of the emerging opportunities that came with the new wave of deep learning and triggered an entire range of new projects in object recognition and other applications. Currently, our team is comprised of more than 100 employees, 15% of whom hold a Ph. D. and half of our employees are actively involved in R&D activities. --- --- ## Posts Accurately identifying individuals is the first step towards a more secure society. In such a digital age security continues being one of the main concerns, especially since we have integrated technology into our everyday lives. Whether to protect sensitive data, to prevent fraudulent activities or to identify criminals, there is always demand for technologies that ensure safer ways of communication. Successfully being used in various government and enterprise applications biometrics can offer all of that and their opportunities are limitless. Security has been one of the main concerns since we integrated technology into our everyday lives. According to the business data platform Statista, the global biometric technologies market was worth 14. 6 billion U. S. dollars in 2018. The market is expected to reach 55. 42 billion U. S. dollars by 2027, following its rapid growth in the coming years and increase in use cases. Whether to protect sensitive data, to prevent fraudulent activities or to identify criminals, there is always demand for technologies that ensure safer ways of communication. Luckily, biometrics can offer all of that and their opportunities are limitless. Biometrics are unique body characteristics that can be used to digitally authenticate an individual. These identifiers can be categorized as physical or behavioral traits. There are several options to choose from when looking to employ them, such as facial or iris recognition, palmprints, fingerprints and voice recognition being the most common examples. The type of biometric authentication used is determined by the goals of the entity deploying biometric validation technology. Needless to say, physiological traits are more stable since they are often non-alterable, except by severe injury or old age, when behavioral ones could be affected by illness or stress. Fingerprint recognition One of the most well-known identifiers, this type of biometrics has been in use since the late nineteenth century after Sir Francis Galton successfully convinced the general public of their reliability for identification. He was the one who provided the first functional fingerprint classification system which,... --- The MINEX III evaluation is a NIST SP 800-76-2 Biometric Specifications for Personal Identity Verification (PIV) U.S. Government program compliance evaluation. It is a successor to the discontinued MINEX Ongoing program. These comments provided by Neurotechnology are based on NIST MINEX III results published on July 31, 2019. The MINEX III evaluation is a NIST SP 800-76-2 Biometric Specifications for Personal Identity Verification (PIV) U. S. Government program compliance evaluation. It is a successor to the discontinued MINEX Ongoing program. In 2015 Neurotechnology's MegaMatcher algorithm was the first to successfully pass the Minutiae Interoperability Exchange (MINEX) III NIST third-party evaluation, demonstrating its compliance with the state-of-the-art standards as well as its interoperability with other vendors' biometric software. In 2017 our algorithm for PC and mobile platforms submission was ranked as the top interoperable matcher and the fourth most accurate native template matcher among all MINEX III compliant matchers. In March 30, 2018 a significant breakthrough in reliability was achieved by successor MegaMatcher submission. It was ranked as: the most interoperable PIV Level 1 MINEX III compliant template generator; the most accurate native PIV Level 2 MINEX III compliant template generator and matcher pair; the second most interoperable PIV Level 1 MINEX III compliant template generator and matcher pair. Later submission from August 2018 has further demonstrated the substantial improvement of fingerprint recognition software for solutions employing biometric on-card comparison. The latest Neurotechnology's recognition software for use with smart cards platforms has been ranked as: the most interoperable PIV Level 1 MINEX III compliant template generator, being the second fastest in the top 10 leaderboard; almost 2 times improved single finger native accuracy PIV Level 2 (comparing to the predecessor on-card comparison... --- In 2019 MegaMatcher SDK palm print matching algorithm has shown the top result at the FVC-onGoing evaluation. The Palm Print Matcher was the most accurate overall and fastest among the five most accurate matchers. Neurotechnology's Palm Print Recognition Algorithm Tops Test At FVC-onGoing The palm print matching engine of MegaMatcher SDK is most accurate overall and fastest among the five most accurate matchers. Vilnius, Lithuania – February 12, 2019 – Neurotechnology, a provider of deep learning-based solutions, robotics and high-precision biometric identification technologies, today reported the latest FVC-onGoing test results for their Palm Print recognition algorithm. The Palm Print Matcher, part of Neurotechnology's MegaMatcher SDK, was ranked as the most accurate for both full and partial palm prints, as the fastest partial palm print matcher and the fastest full-print matcher out of the five most accurate matchers. Neurotechnology's algorithm also has the smallest template size overall, both in full palm print and partial (lower) palm print datasets. "Our expertise in fingerprint recognition technologies carries over to palm print matching," said Dr. Justas Kranauskas, head of the biometric research department for Neurotechnology. "Though the palm print is a larger, more detailed recognition task, our experience in this field allows us to bring the most accurate, highest efficiency application available to the palm print recognition market. " Because of its complexity, palm print template matching requires much more computational time than single or multiple fingerprint matching. Focusing on speed, as well as accuracy, Neurotechnology has developed a palm print matching algorithm that is the fastest partial (lower) palm print matcher and fastest full palm print matcher out of the top five most accurate full palm print matchers in FVC-onGoing. It is suitable for both 1-to-1 (verification)... --- In 2018 Neurotechnology's iris recognition algorithm has been judged by the National Institute of Standards and Technology (NIST) as the second most accurate among the participants. The accelerated version of the algorithm was nearly 50 times faster than any other matcher in the NIST IREX IX evaluation. Neurotechnology's iris recognition algorithms have been judged by NIST as the second most accurate among the IREX IX participants. The accelerated version of the algorithms were nearly 50 times faster than any other matcher in the NIST IREX IX evaluation. NIST Iris Exchange (IREX) IX is an evaluation of automated iris recognition algorithms. The National Institute of Standards and Technology (NIST) has evaluated 46 iris recognition algorithms from 13 commercial organizations and research institutions. The tests were run over operational data for both verification (one-to-one) and identification (one-to-many) tasks. The main goals of the evaluation were: to assess the current state of the art, facilitate research and development, and assess the impact of demographics. We will focus on the current state of the art in the following paragraphs. The evaluation started in April 15, 2016 and continued through 3 submission phases until the final deadline for the third phase on September 1, 2017. During this time we have submitted two different generations of our iris recognition algorithms, namely 9. 0 and 10. 0. The final report from NIST overviews evaluation results for submissions from the second and third phases only. In our case, submissions from the second phase ("Neurotechnology 3" and "Neurotechnology 4") correspond to generation 9. 0 and submissions from the third phase ("Neurotechnology 5" and "Neurotechnology 6") correspond to generation 10. 0. For verification task our final submissions are exactly the same iris recognition algorithms which have already been available to our clients since VeriEye 10. 0 and... --- DR Congo Voter Registration Project uses MegaMatcher ABIS solution. 46.5 million voter records deduplicated, 6 million duplicates and underage records found. Democratic Republic of the Congo Voter Deduplication Project - Case Study MegaMatcher Automated Biometric Identification System (ABIS) an MegaMatcher Accelerator Extreme provided fast and accurate deduplication of 46. 7 million multibiometric voter records, identifying more than 6 million duplicates and 900,000 under-age records. Working with the Independent National Electoral Commission of the Democratic Republic of the Congo, Neurotechnology completed the project in under two months. PDF version The Democratic Republic of the Congo (DRC), in preparation for their 2018 election, wished to have as many voters registered as possible and to have those registrations be an accurate record of all potential voters. With the multibiometric data of 46. 7 million voters in their collected database, the Independent National Electoral Commission (Commission Électorale Nationale Indépendante or CENI) worked with Neurotechnology to deduplicate the registration rolls. Using MegaMatcher ABIS, based on the MegaMatcher Accelerator Extreme multibiometric matching engine, more than 6 million duplicates and more than 900,000 under-age records were identified, and results were achieved in less than two months. The customer: Astride the equator, in the center of Africa, the Democratic Republic of the Congo (DRC), is, by area, the largest country in Sub-Saharan Africa and the 2nd largest country on that continent. With a population of over 86 million, the DRC is the fourth most-populated nation in Africa and the 16th most populated country in the world. The need: Understanding that to have fair and just elections it was essential to verify the registered-voter base of 46. 7 million, CENI... --- In 2018 Neurotechnology has been ranked among 8 most accurate face recognition algorithm vendors out of 39, with tenth most accurate algorithm out of 78 in the FRVT leaderboard. Neurotechnology has been ranked among 8 most accurate face recognition algorithm vendors out of 39, with tenth most accurate algorithm out of 78 in the FRVT leaderboard. The submission was also ranked as one of the best in two difficult scenarios, with second most accurate result on a complex dataset collected from operational photos related to ongoing criminal investigations, and fourth most accurate result with unconstrained, photojournalism-style photos. NIST has started the FRVT Ongoing evaluation of face verification algorithms in February 2017. Since then, 78 algorithms from 39 vendors were tested on 6 datasets of different complexity. Each vendor can submit multiple algorithms once in every three months, but the report takes into account only 2 latest submissions per vendor. Thus, only 62 algorithms are analyzed in the current report from NIST. Modern face recognition algorithms are based on convolutional neural networks, and the easiest way to improve classification accuracy is to use larger neural network models. The figure below shows the accuracy of all tested algorithms and their model size (in bytes) as reported by NIST. The colored dots correspond to all Neurotechnology submissions with the most recent being the most accurate of them. VISA dataset Although six different datasets are used in this evaluation, NIST ranks all algorithms by FRR @ FAR=0. 01 % on VISA dataset. According to the dataset description, the face images have geometry in reasonable conformance with the ISO/IEC 19794-5 Full Frontal image type and pose is generally excellent. The complexity of this dataset... --- In 2017 Neurotechnology fingerprint algorithm was submitted to NIST Proprietary Fingerprint Template Evaluation II. The algorithm's template matching accuracy was among the best participants in most of the experiments. NIST Proprietary Fingerprint Template Evaluation II (PFT II) is one-to-one verification evaluation which measures the performance of fingerprint matching algorithms by utilizing proprietary fingerprint templates. The samples dataset have been increased to 120,000 subjects compared to previous PFT evaluation. Number of experiments was also increased to 33 with different combinations of single and two fingerprints matching. In 2017 Neurotechnology fingerprint algorithm was submitted to NIST Proprietary Fingerprint Template Evaluation II. The algorithm 's template matching accuracy was among the best participants in most of the experiments. Compared to our previous submission 3T, the matching accuracy of the recent submission 3Z (in red) at FMR=0. 0001 improved 1. 18 times on average. In summary, we present accuracy results as FNMR@FMR=0. 0001 for each of 33 experiments: 1-9 correspond to plain-to-plain fingerprints matching on AZLA dataset. 10-18 correspond to plain-to-rolled fingerprints matching on AZLA dataset. 19-27 correspond to rolled-to-rolled fingerprints matching on AZLA dataset. 28-30 correspond to plain-to-plain fingerprints matching on DHS2 dataset. 31-33 correspond to plain-to-plain fingerprints matching on POEBVA dataset. Our latest submission 3Z (in red) is among the most accurate algorithms in all experiments. We also present template extraction and comparison times for seven most accurate recent submissions for all four different dataset: Our latest submission 3Z (in red) is the fastest during enrollment and second fastest during matching of fingerprint templates. It is also the only one which performs template extraction in under one second in average for any tested dataset – the most common requirement for biometric... --- Somaliland government decided to register all Somaliland citizens for the creation of a biometric National Identity Card system. Somaliland government decided to register all Somaliland citizens for the creation of a biometric National Identity Card system. Sahal Tech Solutions selected MegaMatcher Accelerator to provide the high level of security, accuracy and speed required for biometric registration and identification using fingerprint, face and iris biometrics. Biometric registration centers have been set up in every city and village in the country and almost 500,000 registrations were completed during the first months. Read the case study --- The Sri Lanka Bureau of Foreign Employment needed a way to accurately identify and record Sri Lankan citizens working in different countries around the world, as well as eliminate the use of fraudulent passports. The Sri Lanka Bureau of Foreign Employment needed a way to accurately identify and record Sri Lankan citizens working in different countries around the world, as well as eliminate the use of fraudulent passports. Cenmetrix has developed the CenAFIS solution, an Automated Fingerprint ID System that is used together with a passport scanner. Since CenAFIS came online in 2012, more than 100,000 people have been enrolled in the system, with 350 to 450 new enrollments per business day. (more... ) --- The National Electoral Council of Venezuela wanted to update their existing voter registration system with a more open and cost-effective technology. The National Electoral Council of Venezuela wanted to update their existing voter registration system with a more open and cost-effective technology. The old system was built in 2004 and appeared to be expensive to maintain and expand. Ex-Clé has developed and implemented the new integrated biometric platform for the Venezuelan voter registration system using the MegaMatcher SDK and MegaMatcher Accelerator solution. The system was used during the 2012 Venezuelan presidential election and proved its speed and accuracy with biometric data from nearly 18 million registered people. (more... ) --- Indian police departments required a tool for the investigation of criminal activity through the quick and accurate identification of latent fingerprints collected at crime scenes. Indian police departments required a tool for the investigation of criminal activity through the quick and accurate identification of latent fingerprints collected at crime scenes. SecureMantra Technologies has developed the Criminal AFPIS Enterprise Solution using VeriFinger, and then MegaMatcher multi-biometric identification engine with the first deployment in May 2002. Today, police departments in seven Indian states and the National Institute of Criminology and Forensic Science of India are using the solution with more than a million criminal records in the databases. (more... ) --- FpVTE 2012 is the latest and the largest independent evaluation of fingerprint identification technologies conducted by the National Institute of Standards and Technology (NIST). The evaluation used operational fingerprints datasets which contained several million subjects and tested one-to-many identification scenarios with finger combinations varying from single finger to ten fingers. FpVTE 2012 is the latest and the largest independent evaluation of fingerprint identification technologies conducted by the National Institute of Standards and Technology (NIST). The evaluation used operational fingerprints datasets which contained several million subjects and tested one-to-many identification scenarios with finger combinations varying from single finger to ten fingers. These Neurotechnology comments on the NIST report take into account algorithms' accuracy, search time and enrollment time. NIST has also tested RAM usage; however, RAM cost is negligible in large-scale projects with nowadays servers architecture. The FpVTE 2012 submisions were divided into three classes: Class A – single flat fingerprints;Class B – flat tenprints (four-finger slaps and dual thumbs);Class C – 14 print cards (two four-finger slaps, dual flat thumbs and ten rolled fingerprints). Previously, Neurotechnology participated in FpVTE 2003. Class A The Class A image dataset consisted of live-scan single finger captures of the left and right index fingers. Neurotechnology's submission E1 represents MegaMatcher SDK, used for fingerprint processing and MegaMatcher Accelerator (tuned for maximum accuracy) used for template matching. Submission E2 corresponded with an algorithm prototype which is not currently used in any Neurotechnology products. The results show that a system built using MegaMatcher SDK and MegaMatcher Accelerator may achieve one of the fastest matching speeds with good accuracy at the same time. Neurotechnology submissions E1 and E2 are denoted with red color. Class B The Class B image dataset consisted of live-scan identification flat fingerprints, which captured left and right four-finger slaps and both thumbs simultaneously. Neurotechnology's... --- IDDEEA (the Agency for Identification Documents, Registers and Data Exchange) developed the biometric identification system in-house using the MegaMatcher Extended SDK. The system, which was launched in October 2009, uses MegaMatcher components and ensures quality and accuracy required to meet European Union standards. IDDEEA (the Agency for Identification Documents, Registers and Data Exchange) developed the biometric identification system in-house using the MegaMatcher Extended SDK. The system, which was launched in October 2009, uses MegaMatcher components and ensures quality and accuracy required to meet European Union standards. The IDDEEA is an administrative organization within the Ministry of Civil Affairs of Bosnia and Herzegovina and is responsible for the personalization and technical processing of passports, identity cards, driving licenses and other identification documents for the nation's more than 4. 6 million people. (more... ) --- Indra has deployed quick access border control systems based on MegaMatcher in the airports of Madrid-Barajas and Barcelona-El Prat for European citizens. Indra has deployed quick access border control systems based on MegaMatcher in the airports of Madrid-Barajas and Barcelona-El Prat for European citizens. The newly installed systems facilitate the rapid entry into national territory, and therefore the Schengen common European area, to travelers who own a Spanish electronic ID card or a European Community electronic passport. The systems perform a dual biometric test using facial and fingerprint recognition for passenger identity verification. All citizens of the European Union countries, the European Economic Area and Switzerland are eligible to use this system. (more... ) --- Polish Security Printing Works, working closely with the Polish government selected Neurotechnology's VeriFinger fingerprint recognition technology to be the verification engine for all newly issued passports. Polish Security Printing Works, working closely with the Polish government selected Neurotechnology's VeriFinger fingerprint recognition technology to be the verification engine for all newly issued passports. The VeriFinger-based fingerprint system was implemented as a part of the biometric data capture in all 130 passport offices throughout Poland. High performance and flexible licensing options enabled Polish Security Printing Works to quickly obtain, develop and implement the technology. (more... ) --- ---