A beginner’s guide to fingerprint sensors
June 05, 2017
Prior to the iPhone 5s, consumers used to associate fingerprint imaging primarily with law enforcement and high security applications. As the adoption of fingerprint imaging in smartphones grew, users started to perceive fingerprint scanners as a useful and convenient feature from a security point of view. This article examines the dominant fingerprint sensor technologies and discusses some of the key trends in their use.
Most of the mobile phones equipped with a fingerprint scanner use capacitive fingerprint sensors based on conventional CMOS technology. When the user places their finger on the sensor, the sensor is able to register the subtle differences in capacitance between the finger’s ridges and valleys. A map is then created that consists of the user’s fingerprint; it is then matched against the user’s fingerprint image template, which in most cases is stored on the mobile phone. This function is called 1:1 matching where one image is matched to one template. The fingerprint image template is created when the user registers their fingerprint which activates the fingerprint imaging feature on the device. The size of a capacitive sensor is usually in the range of 8 x 8 mm – it is as small as possible for cost reasons but large enough to capture enough features in a single image to carry out the matching. This is because the matching accuracy of a fingerprint sensor is strongly influenced by its resolution and size. The resolution of most capacitive fingerprint sensors in mobile phones is around 500 dpi.
Historically the security requirements for authenticating a user on a mobile phone was low, because authenticating the wrong user from time to time (i.e. having a higher false acceptance rate - FAR), would only result in accessing a phone owner’s contact list and possibly their email. As the use of mobile phones evolved to authenticate payments and carry out online transactions, the security requirements for mobile phones and other smart devices became a concern. Technologists hence started testing the robustness of the security of capacitive sensors by trying to crack the system through the use of fingerprint moulds. Many succeeded with capacitive sensors because they generate the fingerprint pattern from the surface of the skin. Therefore any material that mimicked the same fingerprint undulations and skin properties was able to be authenticated by the system. Hence the debate started around the detection of fake fingerprints and which technologies were good enough to have low FAR.
Another common sensor technology is optical fingerprint imaging which is mainly used in border control and high security applications. Conventional optical scanners use a small CMOS image sensor which is usually a few square millimetres with a complex prism setup that is optimised to create an optical path. The latter enlarges the area of the image captured by the fingerprint sensor. Flat panel based technologies including amorphous silicon, polysilicon and organic transistors over large areas are also used for making optical sensors in order to avoid the need for prisms. In this case the sensor and the sensitive area are the same size. This is not viable with a CMOS sensor due to cost reasons. Optical sensors are therefore more expensive compared with capacitive sensors due to their larger size and design complexity.
Optical sensors dominate in applications that require higher security due to their ability to image deeper into the skin through the use of different wavelengths to image skin pores and differentiate a fake finger from a real one. Additionally they make it easier to identify people with poor fingerprints caused by dry skin, wet skin or worn-out fingerprints. This is not possible with most capacitive fingerprint sensors. Optical sensors are also larger in size and can image more fingers at once, meaning that more information can be acquired in order to enable matching against a database. This is called the 1:N matching and is predominantly done within the context of border control, law enforcement and, in some cases, access control for high security facilities. Fingerprint sensors used in border control and law enforcement are required to have FBI appendix F certification which defines certain level of performance.
Recently there has been a trend towards the integration of optical fingerprint sensors in consumer electronics for two key reasons; firstly an aesthetic one in order to achieve a button free fingerprint enabled display on the smart device, and secondly to increase the fingerprint sensor area on the device to make it more secure particularly for financial transactions. Brands like Apple, Samsung and others are racing towards implementing this in their next generation products.
There are other candidate fingerprint sensor technologies like ultrasonic and thermal sensors that are being developed however their use has not yet been demonstrated in products.
Whilst the above technologies have all been demonstrated as rigid sensors, there is a trend to move to thin, flexible, light-weight and robust fingerprint sensors that can easily be integrated into products and make them more mobile and user-friendly. Such flexible fingerprint sensors have been demonstrated in smartcards as an additional user-authentication feature to pin codes. However, their true value would be for applications that require the integration of large area fingerprint sensors such as smartphones, tablets and other consumer electronics as well as mobile fingerprint scanners for law enforcement and remote border control applications. For more applications of flexible fingerprint sensors please see my article “Five industries that will benefit from flexible fingerprint sensors”.
Ultimately the fingerprint sensor technology that will become most widely used will be the one that is secure, cost effective and user friendly.
If you want to learn more about FlexEnable’s fingerprint and vein sensor solutions for biometric applications, contact us at firstname.lastname@example.org.