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The photo response non-uniformity (PRNU) of a sensor can be useful to enhance a biometric systems security by ensuring the authenticity and integrity of images acquired with a biometric sensor, e.g. by performing a source device identification. Previous studies regarding the feasibility of this application have been conducted on the CASIA-Iris V4 database by studying the differentiability of the sensors...
Similar to the impact of ageing on human beings, digital image sensors develop ageing effects over time. Since these imager's ageing effects (commonly denoted as pixel defects) leave marks in the captured images, it is not clear whether this affects the accuracy of iris recognition systems. This paper proposes a method to investigate the influence of sensor ageing on iris recognition by simulative...
Iris is the Optimum Biometric-trait present in Biometrics Security. Our emphasis on this paper is to obtain efficient, fast and robust algorithm set for iris detection. There are number of algorithms proposed for the efficient result but fails due to limitations. We tried in this paper to make, an efficient combination of the best schemes of normalization, corner detection, feature extraction and...
It has great significance to efficiently distinguish the type of the samples' data in the decision table after the discretization for the course of machine learning and data mining afterwards. This paper puts forward an annotation method of distinguishing the data type based on attributes importance and the samples entropy, and processed the simulation test using part of the UCI database which was...
Iris recognition has been recently given greater attention in human identification and it's becoming increasingly an active topic in research. This paper presents a personal identification method based on iris. The Method includes three steps. In the first one, the eye image is processed in order to obtain a segmented and normalized eye image by applying an integrodifferential operator, Hough transform...
Biometrics has become more and more important in security applications. In comparison with many other biometrie features, iris recognition has very high recognition accuracy. Successful iris recognition matching depends on how similar the stored template in database is compared with the introduced template. The main objective of this paper is to introduce a high performance scheme for iris recognition...
Understanding people attentional focus can be useful for several applications. One important challenge in this area is to determine the iris position in image/video in order to estimate gaze behavior. To this end, this paper presents a robust and non-intrusive method to locate human iris position in low resolution grayscale images, in real-time. The method requires the previous knowledge of the face...
Accurate segmentation is a crucial phase in the implementation of an iris recognition system. In this paper we investigate a novel technique for iris segmentation. Morphological operations and area computation are applied together with other iris segmentation techniques in order to increase the speed and accuracy of the preprocessing phase. A rough approximation of the pupil's location is first determined...
In this work, we present a local-global (LG) graph methodology for iris based biometric authentication. Local-global (LG) graph method adds local part information into a global graph. Local graphs of the pre-processed iris images are first calculated by feature extraction and combined to form a global graph that is stored in a database for the purpose of authentication. The global graph of the presented...
One of the basic steps in iris-based human identification is the exact localization of the iris. Typically, the Hough transform is used for this purpose. Hough transform is very sensitive to the noise and the exact circular iris shape. Our goal is to present a stable and fast method for accurate iris localization within the eye image. In the presented method, the use of a recursive algorithm is suggested...
In this paper, we proposed an anti-competitive learning neural network scheme against mining of knowledge from databases. Neuron weights were trained by competitive learning in neural network and used with noise to harass the original database. The data mining process in anti-competitive learning will only allow data that contains unimportant knowledge to be mined. Experimental results showed that...
Data mining is a technique to search potential valuable information from databases. Preventing personal data and high security data therefore pose a difficult task to IT experts. In this paper, we propose a novel anti-data mining (ADM) database security scheme, that protect against data mining. The scheme makes use of hierarchical clustering where noise is added to change the cluster structure of...
In this paper, we evaluate the effects of time separation between acquisitions in iris recognition. We use for our experiments a publicly available iris recognition system and the BiosecurID database, containing 8128 iris images of 254 individuals acquired in four acquisition sessions, separated by one to four weeks between consecutive sessions. Reported results show that time separation between iris...
Iris biometry has been proposed as a sound measure of personal identification. The iris, however, can change in response to physiological processes, medications and disease states. To develop a system of iris recognition that is reliable requires identifying both the features that may alter and those that are stable, and finding an accurate way of localising these. The major iris characteristics from...
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