Takuji Maeda

Fingerprint Authentication Device Based on Optical Characteristics Inside a Finger

Fingerprint is the most popular modality that is widely used in various authentication applications; PC logon, gate access control systems, and so on. The reason can be considered that fingerprint can achieve the best balance among authentication performance, cost, size of device, and ease of use. However, most of fingerprint authentication devices have some problems to be solved. One is that captured images are easily affected by the condition of finger surface and it can degrade authentication performance. The other is that the problem of impersonation by artificial gummy fingers has been pointed out. To solve those problems, we developed a new fingerprint authentication device that has a novel sensing principle. This device forms a image of fingerprint pattern based on optical characteristics of a finger’s interior by scattered transmission light. The images so obtained are unaffected by the condition of finger surface such as dry or moist fingers or operating environment, and enable stable authentication processes. And it can differentiate between real fingers and fake gummy fingers made from gelatin or other material using optical characteristics. Because this device utilizes the optical characteristics inside a finger, it has possibility to achieve higher authentication performance by combining multiple characteristics of a finger’s interior as a modality. In this paper, we describe the sensing principle and process algorithm of this device.

Characteristics of the Identification Algorithm Using a Matching Score Matrix

Biometrics authentication can be achieved by either verification or identification. In terms of convenience, identification are superior since a user does not have to input his/her ID number. However, it must be capable of searching the database storing user enrollment templates at high speed. To meet this need, we proposed an identification algorithm. In this paper, we describe our proposed method and discuss its characteristics of response speed using some simulation results. It is shown that response speed depends on the way to select enrollment data.

Optimization of illuminating system to detect optical properties inside a finger

Biometrics performs personal authentication using individual bodily features including fingerprints, faces, etc. These technologies have been studied and developed for many years. In particular, fingerprint authentication has evolved over many years, and fingerprinting is currently one of worlds most established biometric authentication techniques. Not long ago this technique was only used for personal identification in criminal investigations and high-security facilities. In recent years, however, various biometric authentication techniques have appeared in everyday applications. Even though providing great convenience, they have also produced a number of technical issues concerning operation. Generally, fingerprint authentication is comprised of a number of component technologies: (1) sensing technology for detecting the fingerprint pattern; (2) image processing technology for converting the captured pattern into feature data that can be used for verification; (3) verification technology for comparing the feature data with a reference and determining whether it matches. Current fingerprint authentication issues, revealed in research results, originate with fingerprint sensing technology. Sensing methods for detecting a persons fingerprint pattern for image processing are particularly important because they impact overall fingerprint authentication performance. The following are the current problems concerning sensing methods that occur in some cases: Some fingers whose fingerprints used to be difficult to detect by conventional sensors. Fingerprint patterns are easily affected by the fingers surface condition, such noise as discontinuities and thin spots can appear in fingerprint patterns obtained from wrinkled finger, sweaty finger, and so on. To address these problems, we proposed a novel fingerprint sensor based on new scientific knowledge. A characteristic of this new method is that obtained fingerprint patterns are not easily affected by the fingers surface condition because it detects the fingerprint pattern inside the finger using transmitted light. We examined optimization of illumination system of this novel fingerprint sensor to detect contrasty fingerprint pattern from wide area and to improve image processing at (2).

Analysis of response performance characteristics for identification using a matching score generation model

To make person authentication systems be more useful and practical, we have developed an identification algorithm, and also showed that the authentication accuracy depends on response performance. Current identification algorithm employs a comparison computation function that is optimized for one-to-one comparison. By optimizing a comparison computation function, however, it might be possible to improve response performance. In this paper, we describe design guidelines for a comparison computation function for improving the response performance of the identification. To show the guidelines, we clarify the relation between the characteristics of a matching score distribution and response performance using a matching score generation model, and also demonstrate the effectiveness of the design guidelines with a simulation using an example of another comparison computation function.