The Research Method Of Eyelash, Eyelid And Reflection Detection

With the information times coming and the development of the network technology, based mainly on token or password system can't meet the requirement of high effect and security. So people make for biometrics technology which has been the new growth area in the economy. As iris identification is one of potential biometrics technologies, it has been gradually applied to safety fields. Iris identification is based on iris texture to identify persons, and it is one of most accurate biometrics technologies. Because the iris recognition is in the ascendant abroad, and in domestic it is just on the beginning. So, it is important and valuable to analyze processing the iris imaged soundly.In an iris recognition system, the major research object is the iris texture. However, under the high reliable system, the captured iris image contains not only the iris information, but also the sclera, eyelid, eyelash, reflection, and so on. If the disturbed factors are recognized as the iris feature into the iris image coding, there will be false iris code. Therefore, this can greatly affect the performance of iris recognition. This paper analyzes different noises in the iris region and takes different methods to eliminate different noises, so we can avoid the noise region in the feature extraction and matching, meanwhile improve the accuracy rate of iris recognition.To reduce the influence of eyelash noise and improve discriminability in iris recognition, based on the canny operator, developed an eyelash edge detection algorithm to detect eyelash in the image. One sector in the outer circularity of iris is used to represent the region of eyelash occlusions. Excluding the pupil and the sector, the rest of the outer circularity is the effective region of iris. The eyelid noise contains the upper eyelid and the lower eyelids, the edges of which are close to parabolic. The traditional method that combines horizontal edge detection with Sobel operator and parabolic Hough transform are used to find the upper and lower eyelids. The reflection detection can be classified into two steps: first, obtain the points of higher intensity, which belong to reflection and eyelid; second, they are identified as points in a reflection or in an eyelid, according to the characteristic of lower intensity around the reflection. Extensive experimental results show that the algorithm is effective, which not only has high precision, but also has good robustness.Our experimental results demonstrate that the sector contains all eyelash,eyelid and sclera pixels in the outer circularity; the algorithm can detect the eyelash effectively and can improve the classification and discriminability of iris patterns and the rate of iris recognition.