Patent Application
20190384957
This application is related to Canadian patent application number 2,952,510 filed Dec. 23, 2016. No priority is claimed.
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The invention pertains to the capture and quality assessment of friction ridge impressions i.e. prints from the fingers and palms of human hands.
Friction ridge skin is most commonly known as the skin that is found on the palms of the hands and the bottoms of the feet of humans and other primates. This type of skin is corrugated, which means it features tiny furrows or valleys between ridges. These ridges provide friction that helps the hands and fingers grip objects. These ridges also provide the feet with a stable surface to walk without slipping and sliding on smooth surfaces. The ridge patterns have distinctive features such as ridge endings (the points at which friction ridges terminate) and bifurcations (the points at which one friction ridge divides into two friction ridges). Note that the terms fingerprint, palm print and footprint refer to an impression left by the friction skin or an image of the friction skin rather than the anatomical structure itself. For the remainder of this document the term “print” will mean fingerprint and/or palm print. The prints may be from any of the ten fingers of the left and right hands, and any components of the palms of the right and left hands.
A digital image record of a person's fingerprint or palm print is captured either directly using a livescan device (see
Many organizations including but not limited to government agencies, law enforcement agencies, and commercial corporations at the international, national and local level compile databases that contain fingerprint and/or palm print records of individuals. These print databases are major components of automated fingerprint identification systems (AFIS) and automated fingerprint verification (AFV) systems.
Automated fingerprint (or palm print) identification is the process of automatically matching one or many unknown prints against a database of known prints. In some cases unknown prints are also included in the database. This is often the case for law enforcement applications where unknown prints from unsolved cases are included in a database of known criminal prints. An automated fingerprint identification system (AFIS) consists of a database of prints plus matcher software that is used to search a print against the database to try to find the closest match or matches. This is sometimes called a 1:N search where “N” represents the number of records in the database. AFIS is used by law enforcement agencies for criminal identification initiatives, namely identifying a person suspected of committing a crime or linking a suspect to other unsolved crimes.
Automated fingerprint verification (AFV) is a closely related technique used in applications such as attendance and access control systems. It also consists of a database of prints plus matcher software, however in this case the matcher is verifying that the prints submitted for an individual match the prints for that individual contained in the database. This verification search is sometimes called a 1:1 search. On a technical level, verification systems verify a claimed identity whereas identification systems determine identity based solely on prints.
Both AFIS and AFV have been implemented in large-scale civil identification projects. The chief purpose of a civil AFIS or AFV is to prevent multiple enrollments in an electoral, welfare, driver licensing, or similar system. Another benefit of a civil AFIS is its use in background checks for job applicants for highly sensitive posts and educational or volunteer personnel who have close contact with children. Background AFIS checks are typically conducted to determine if an individual has a criminal record.
Digital print images are typically submitted to AFIS and MV databases to i) add the images to the database to establish a baseline print record of an individual in the print database or ii) search the print database to determine if the submitted print record matches an existing entry in the print database.
An ideal digital print image of friction ridge skin has clear and distinct ridges and valleys. It is known that the matcher software algorithms of AFIS and AFV systems are sensitive to fingerprint image quality as indicated by features including but not limited to:
Print images to be submitted to databases for AFIS, AFV or other applications must be of suitable quality for comparison and searching with matcher software. The prints must be captured in digital format for submission to and storage in a database. As stated previously, a digital image of a person's fingerprint or palm print is captured either directly using a livescan device (see
A card used to capture inked prints of all ten fingers is typically called a tenprint card. A tenprint card is illustrated in
A livescan is a device used for scanning live prints electronically for submission to a print database. The process of obtaining the prints by way of livescan typically employs rolling an individual's fingers onto a glass platen above a sensor unit that records the rolled prints or by placing fingers or palms flat onto the platen to obtain flat prints. There are also contactless systems that do not require fingers or palms to touch a platen. Livescan sensor technologies include but are not limited to:
The Biometric Submission System is a friction ridge image capture system consisting of a computer program, a livescan device (see
There are problems capturing fingerprints/palm prints with livescan devices. The Canadian Friction Ridge Working Group has published a position statement noting the detrimental impact on fingerprint quality due to anomalies (blurring and stitching) caused by some livescan devices (Canadian Friction Ridge Working Group, “Position statement—Impact of Livecan Anomalies on Friction Ridge Identification” Sep. 8, 2014). The Eurodac database of EU asylum seeker fingerprints has noted that up to 20% of fingerprint submissions are found to be unreadable (Eurodac Supervision Coordination Group, “Report on the coordinated inspection on unreadable fingerprints” May 2013). A number of studies have found that dermatologic diseases which affect 5% of the population render fingerprints to be unreadable by livescan devices (Drahansky, M., Brezinova, E., Hejtmankova, D., and F. Orsag, “Fingerprint Recognition Influenced by Skin Diseases” Intn'l J. of Bio-Science and Bio-Technology V.2 No. 4 Dec. 2010: 11-20; Lee, C. K., Chang, C. C., Johar, A., Puwira, O., and B. Roshidah, “Fingerprint Changes and Verification Failure Among Patients with Hand Dermatitus” JAMA Dermatol. 2013; 149(3):294-299). Inked prints are typically better quality in such instances.
In addition, sometimes it is not possible for an individual to travel to the location of a livescan station so the only option is for the individual to mail or courier a tenprint card to be scanned via cardscan or digitally photographed in order to submit their prints.
The preferred embodiment of the Biometric Submission System (BSS) includes a computer program implemented on a computer (see
In comparison to livescan alone, the BSS increases the probability of capturing prints of quality suitable for submission to a database by providing both livescan and a means of obtaining digital images of inked prints.
The BSS computer program includes a GUI (graphical user interface) and manages fingerprint image capture, entry of print donor data, storage of images and data, formatting of images and data into a submission file and transmission of the submission file to a database. The computer program also includes:
The BSS computer program integrates the process of capturing prints via livescan and digitization of inked prints into one workflow to increase the probability of capturing higher quality print images in comparison to livescan alone.
The typical print capture workflow with preferred embodiment of the BSS is as follows:
