O introduction
IRIS is located on the eye surface black pupil and white sclera visible between circle, to a certain frequency of near-infrared, presents a rich texture information, such as spotted striped, fine lines, Coronal, crypt and other physiological details feature.
The visible human IRIS tissue structure depends on the embryonic period germ layer infants depends, in the crowd of distribution may be random or chaotic, but a born life stability, but everyone's iris absolutely different. Statistics show that IRIS hundred degrees, even the same genotype, phenotype expression of IRIS is irrelevant. Because the human eye IRIS unique texture image suitable for automatic identification, so it is an efficient, accurate, not replication. The basic principle is by comparing the iris image similarity between characteristics to determine the identity of the human body, at its core, the computer will be a large amount of many algorithms, using pattern recognition, image processing, and other methods on the eye's iris texture features are described and match (such as the early application of Gabor Wavelet coding of IRIS, Iris with Han Min distance on templates to match), enabling automatic identification of the human body.1 the composition of the iris recognition system
Iris recognition system consists of software systems and hardware systems, software systems that IRIS information processing system to realize the iris image processing, user registration, user identification, Iris Iris image storage management, storage management features.
Form the block diagram shown in Figure 1. Hardware system including Iris image acquisition system and to support IRIS information processing system running on the hardware environment.
Current market more mature computer core algorithm is the University of Cambridge, United Kingdom Daugman technology of the University of bath and the Chinese Academy of Sciences MJRLIN technology.
This experimental system adopts United Kingdom MIRLIN technology of the University of bath.2 restricted conditions of the iris image acquisition technology analysis
International Association of eye safety standards require the iris image acquisition devices for real-time automatic non-invasive optical imaging device of IRIS.
The world's leading iris lens employs more than 640 × 480 pixel CMOS progressive scan cameras, which in human IRIS diameter range requires at least 100 pixels collection point above, to the extent possible, preserve the original Iris image characteristics. According to the ISO/IEC 19794-6 image standard, while ensuring that the dark environment photography needs, select the light source wavelength 720 ~ 900nm of near-infrared sources, radiation power < 0.5mW/cm2, does not have the injury to the eyes. Camera transfer rate is set to 251 frame/s to ensure real time transmission of the video stream. Filming process, central processing module on every frame image for real-time analysis until the frame image meets the criterion, and at the same time, the data frame is transmitted to the iris recognition processor core module makes the judgement. Overall hardware design schema as shown in Figure 2.
In total 352730 testing we found the actual system Iris image acquisition for the success of several important limiting factor including human-computer interaction, light intensity, and other system outside limits.
Therefore the design of the applicability of the system is very important. To achieve the automatic intelligent IRIS acquisition, through tens of thousands of experiments, we sum up out of the system is designed with the following considerations:2.1 distance sensor
First of all, the camera module to an external user distance inductive sensors for monitoring individual existence.
Sensor selection for the contact type (such as a card reader or password switch modules, etc.) and non-contact type modules (such as infrared sensors or shoulders probe module, etc.), considering that the system for future compatibility, and CPU interface design is recommended to use GPIO connections.
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