A comparative study on multiple participants was undertaken to quantify the ability of a multispectral imaging
fingerprint sensor to perform reliable biometric matching in the presence of extreme sampling conditions. These extreme
conditions included finger wetness, dirt, chalk, acetone, bright ambient light, and low contact pressure during image
acquisition. The comparative study included three commercially available total internal reflectance sensors, run in
parallel with the multispectral imaging sensor and under identical sampling conditions. Performance assessments
showed that the multispectral imaging sensor was able to provide fingerprint images that produced good biometric
performance even under conditions in which the performance of the total internal reflectance sensors was severely
degraded. Additional analysis showed that the performance advantage of the multispectral images taken under these
conditions was maintained even when matched against enrollment images collected on total internal reflectance sensors.
Fingerprint systems are the most widespread form of biometric authentication. Used in locations such as airports and in PDA's and laptops, fingerprint readers are becoming more common in everyday use. As they become more familiar, the security weaknesses of fingerprint sensors are becoming better known. Numerous websites now exist describing in detail how to create a fake fingerprint usable for spoofing a biometric system from both a cooperative user and from latent prints. While many commercial fingerprint readers claim to have some degree of spoof detection incorporated, they are still generally susceptible to spoof attempts using various artificial fingerprint samples made from gelatin or silicone or other materials and methods commonly available on the web. This paper describes a multispectral sensor that has been developed to collect data for spoof detection. The sensor has been designed to work in conjunction with a conventional optical fingerprint reader such that all images are collected during a single placement of the finger on the sensor. The multispectral imaging device captures sub-surface information about the finger that makes it very difficult to spoof. Four attributes of the finger that are collected with the multispectral imager will be described and demonstrated in this paper: spectral qualities of live skin, chromatic texture of skin, sub-surface image of live skin, and blanching on contact. Each of these attributes is well suited to discriminating against particular kinds of spoofing samples. A series of experiments was conducted to demonstrate the capabilities of the individual attributes as well as the collective spoof detection performance.
The level of performance of a biometric fingerprint sensor is critically dependent on the quality of the fingerprint images. One of the most common types of optical fingerprint sensors relies on the phenomenon of total internal reflectance (TIR) to generate an image. Under ideal conditions, a TIR fingerprint sensor can produce high-contrast fingerprint images with excellent feature definition. However, images produced by the same sensor under conditions that include dry skin, dirt on the skin, and marginal contact between the finger and the sensor, are likely to be severely degraded. This paper discusses the use of multispectral sensing as a means to collect additional images with new information about the fingerprint that can significantly augment the system performance under both normal and adverse sample conditions. In the context of this paper, "multispectral sensing" is used to broadly denote a collection of images taken under different illumination conditions: different polarizations, different illumination/detection configurations, as well as different wavelength illumination. Results from three small studies using an early-stage prototype of the multispectral-TIR (MTIR) sensor are presented along with results from the corresponding TIR data. The first experiment produced data from 9 people, 4 fingers from each person and 3 measurements per finger under "normal" conditions. The second experiment provided results from a study performed to test the relative performance of TIR and MTIR images when taken under extreme dry and dirty conditions. The third experiment examined the case where the area of contact between the finger and sensor is greatly reduced.
Automated identification systems based on fingerprint images are subject to two significant types of error: an incorrect decision about the identity of a person due to a poor quality fingerprint image and incorrectly accepting a fingerprint image generated from an artificial sample or altered finger. This paper discusses the use of multispectral sensing as a means to collect additional information about a finger that significantly augments the information collected using a conventional fingerprint imager based on total internal reflectance. In the context of this paper, “multispectral sensing” is used broadly to denote a collection of images taken under different polarization conditions and illumination configurations, as well as using multiple wavelengths. Background information is provided on conventional fingerprint imaging. A multispectral imager for fingerprint imaging is then described and a means to combine the two imaging systems into a single unit is discussed. Results from an early-stage prototype of such a system are shown.
This paper describes a new biometric technology based on the optical properties of skin. The new technology can perform both identity verification and sample authenticity based on the optical properties of human skin. When multiple wavelengths of light are used to illuminate skin, the resulting spectrum of the diffusely reflected light represents a complex interaction between the structural and chemical properties of the skin tissue. Research has shown that these spectral characteristics are distinct traits of human skin as compared to other materials. Furthermore, there are also distinct spectral differences from person to person. Personnel at Lumidigm have developed a small and rugged spectral sensor using solid-state optical components operating in the visible and very near infrared spectral region (400-940nm) that accurately measures diffusely reflected skin spectra. The sensors are used for both biometric determinations of identity as well as the determination of sample authenticity. This paper will discuss both applications of the technology with emphasis on the use of optical spectra to assure sample authenticity.