Takafumi Miyatake

Feature extraction of finger-vein patterns based on repeated line tracking and its application to personal identification

Abstract.We propose a method of personal identification based on finger-vein patterns. An image of a finger captured under infrared light contains not only the vein pattern but also irregular shading produced by the various thicknesses of the finger bones and muscles. The proposed method extracts the finger-vein pattern from the unclear image by using line tracking that starts from various positions. Experimental results show that it achieves robust pattern extraction, and the equal error rate was 0.145% in personal identification.

Extraction of Finger-Vein Patterns Using Maximum Curvature Points in Image Profiles

A biometrics system for identifying individuals using the pattern of veins in a finger was previously proposed. The system has the advantage of being resistant to forgery because the pattern is inside a finger. Infrared light is used to capture an image of a finger that shows the vein patterns, which have various widths and brightnesses that change temporally as a result of fluctuations in the amount of blood in the vein, depending on temperature, physical conditions, etc. To robustly extract the precise details of the depicted veins, we developed a method of calculating local maximum curvatures in cross-sectional profiles of a vein image. This method can extract the centerlines of the veins consistently without being affected by the fluctuations in vein width and brightness, so its pattern matching is highly accurate. Experimental results show that our method extracted patterns robustly when vein width and brightness fluctuated, and that the equal error rate for personal identification was 0.0009%, which is much better than that of conventional methods.

IMPACT: an interactive natural-motion-picture dedicated multimedia authoring system

A new approach to achieving a natural-motion-picture dedicated multi-media authoring system is proposed. The main point of this approach, discussed in this paper, is that the user’s environment or interface is improved to encourage user’s creativity, with image processing and recognition technology. According to the discussion, a prototype motion picture authoring system dtat has several image-processing functions is developed. The newly developed functions include object extraction of the picture, semi-automatic visualization of motion pictures structure, and certain descriptions of the scene. Result of using the prototype shows the appropriateness of the proposed approach.

Automatic structure visualization for video editing

We developed intelligent functions for the automatic description of video structure, and visualization methods for temporal-spatial video structures obtained by these functions as well as for the functions. The functions offer descriptions of cut separations, motion of the camera and filmed objects, tracts and contour lines of objects, existence of objects, and periods of existence. Furthermore, identical objects are automatically linked. Thus the visualization methods supported by object-links allow users to freely browse and directly manipulate the structure including descriptions and raw video data.

Automatic scene separation and tree structure GUI for video editing

INTRODUCTION Through the discussion with the users of cument nonlinear editing system, we found that they have a common complaint. That is a manual scene cutting process as a preparation for the nonlinear icon based editing. Users also request a method to see the total video structure in several levels of detail for more effective video editing. We propose an approach to integrate image recognition technology into nonlinear video editing system. It consists of three concepts; automatic scene separation [2] during disk recording, quick review with micon [1], and tree structure story editing. This approach is the exact sohttion for the complaint of the current system users. The automatic scene separation removes time consuming manual separation process and user can immediately start editing after the hard disk recording. The quick review with micon is a quick and convenient shot comparison method. The tree structure story editing provides a method to edit video structure in several different detail levels and relieves the constrain of limited size of the window.

A position recognition algorithm for semiconductor alignment based on structural pattern matching

The authors propose a position recognition algorithm that can be used for future automated production of high-density semiconductor devices. It consists of a position detection method based on a pattern structure which is expressed as the distribution of characteristic local patterns, and an adaptive thresholding method based on an evaluation index which represents the binary state of characteristic local patterns. The validity and effectiveness of the algorithm are confirmed by experimentation with actual semiconductor chip patterns. High-speed processing of the algorithm is possible by using an image processor with simple matching hardware. >

Contour representation of binary images using run-type direction codes

Abstract.This paper proposes a fast and high-definition contour-tracing algorithm for digitized binary images. Only the coordinates of white-to-black and black-to-white transition points on each scan line are used as data for the contour tracing. The resulting description of the contour is the combined set of ten newly developed run-type direction codes. The code is determined automatically by an automaton while the horizontal coordinates of two transition points in the two adjacent scan lines are compared. The processing speed of this algorithm depends on the number of transition points of an image, and, thus, it has the advantage over conventional algorithms, where the speed usually depends on the number of pixels. A high-definition-type contour description is obtained and complete restoration of the original image is possible.

Finger-vein authentication based on deformation-tolerant feature-point matching

A novel method for finger-vein authentication based on feature-point matching is proposed and evaluated. A finger-vein image captured by infrared light contains artifacts such as irregular shading and vein posture deformation that can degrade accuracy of finger-vein authentication. Therefore, a method is proposed for extracting features from vein patterns and for matching feature points that is robust against irregular shading and vein deformation. In the proposed method, curvature of image-intensity profiles is used for feature point extraction because such image profiles are a robust feature against irregular shading. To increase the number of feature points, these points are extracted from any positions where vein shape is non-linear. Moreover, a finger-shape model and non-rigid registration method are proposed. Both the model and the registration method correct a deformation caused by the finger-posture change. It is experimentally shown that the proposed method achieves more robust matching than conventional methods. Furthermore, experiments on finger-vein identification show that the proposed method provides higher identification accuracy than conventional methods.

Knowledge-based multi-media database management system and its application to map information systems

A structure of a multimedia database management system that enables inferential retrieval and automatic construction is proposed. It consists of three parts, namely, a knowledge base at the top, a relational manager in the middle, and a media-oriented manager at the bottom. An automatic recognition and data input method for map figure data and an automatic database construction method and renewal capability are introduced. The effectiveness of these methods has been confirmed by applying them to a prototype map-based system for utility management.<<ETX>>

Personal Authentication Analysis Using Finger-Vein Patterns in Patients with Connective Tissue Diseases--Possible Association with Vascular Disease and Seasonal Change.

Objective To examine how connective tissue diseases affect finger-vein pattern authentication. Methods The finger-vein patterns of 68 patients with connective tissue diseases and 24 healthy volunteers were acquired. Captured as CCD (charge-coupled device) images by transmitting near-infrared light through fingers, they were followed up in once in each season for one year. The similarity of the follow-up patterns and the initial one was evaluated in terms of their normalized cross-correlation C. Results The mean C values calculated for patients tended to be lower than those calculated for healthy volunteers. In midwinter (February in Japan) they showed statistically significant reduction both as compared with patients in other seasons and as compared with season-matched healthy controls, whereas the values calculated for healthy controls showed no significant seasonal changes. Values calculated for patients with systemic sclerosis (SSc) or mixed connective tissue disease (MCTD) showed major reductions in November and, especially, February. Patients with rheumatoid arthritis (RA) and patients with dermatomyositis or polymyositis (DM/PM) did not show statistically significant seasonal changes in C values. Conclusions Finger-vein patterns can be used throughout the year to identify patients with connective tissue diseases, but some attention is needed for patients with advanced disease such as SSc.