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In order to overcome the impact of complex illumination environment and head movement, a novel eye state recognition algorithm is proposed in this paper, which is based on feature level fusion. Firstly, Pseudo Zernike feature was found can be used to overcome the impact of head movement and Gabor feature can be used to overcome the impact of illumination changing. Then we got the fusion feature by...
An iris recognition requires parametric modeling texture. The extracted model should characterize the individual corresponding to considered iris. Such a model is often referred to as biometric signature. Several approaches to uniquely specify an iris by extracting parameters characteristic of its texture exist in the literature. An original approach based on an analysis by the Meyer wavelet of the...
Sclera blood veins have been investigated recently as a biometric trait which can be used in a recognition system. The sclera is the white and opaque outer protective part of the eye. This part of the eye has visible blood veins which are randomly distributed. This feature makes these blood veins a promising factor for eye recognition. The sclera has an advantage in that it can be captured using a...
Iris recognition is effective biometric technique that gained attention in past 20 years. Over past few years many techniques and algorithms are proposed for effective iris recognition under various constraints. Low constraint IRIS recognition is still an area where considerable work needs to be done and there is huge scope to do. This paper discusses about various techniques proposed, the constraints...
Recently, Gait recognition has gained significant attention. It is the identification of individuals in a video sequences, the recognition method is by the way they walk. Active Energy Image (AEI) is a more efficient represent method than Gait Energy Image (GEI), Gabor wavelet is used in face recognition successfully, so we use the Gabor wavelet to extract the amplitude spectral of AEI, research the...
Multimodal Biometric systems have proved more secure as compared to unimodal systems. Multimodal fusion can be achieved by using three approaches which are Feature-level fusion, Score-level fusion and Decision-level fusion. This paper presents an approach which fuses left and right iris using feature level fusion using Haar wavelet, Cosine wavelet and Haar-Cosine Hybrid wavelet followed by Thepade's...
This paper introduces an iris classification system using FFNNGSA and FFNNPSO. This iris identification system consists of localization of the iris region, normalization, feature extraction and then classification as a final stage. A Canny Edge Detection scheme and a Circular Hough Transform are used to detect the iris boundaries. After that the extracted IRIS region is normalized using Daugman rubber...
Iris is unique for each person, so that it can be used as one alternative solution for human identification. In this study, an iris recognition system is developed to automatically identify a person by using eye image data. Firstly, iris area of eye image is detected using Canny Edge Detection and Hough Transform methods. Secondly, texture feature of iris image is extracted using statistical moments...
In previous paper score level fusion performance is tested with various matching score proportions with Iris and Palm print images. Here feature level fusion is done using fractional energy of transform with Iris and Palm print biometric traits. The benefit of energy distribution of transforms in higher coefficients is taken here to reduce the feature vector size of image. Iris and Palm print are...
In this paper, we explore the applicability of first and second order monogenic Steerable Riesz wavelet components for iris recognition. These wavelets provide powerful mechanism to extract the invariant as well as covariant local variations of iris patterns. Unlike other existing methods where sole iris (either left or right) is used for recognition, in our work, we extract the features from both...
Now, gait recognition for identification has received more and more attention from biometrics researchers. Gait Energy Image(GEI) is an efficient represent method and Gabor wavelet has many excellent property, so we use the Gabor wavelet to extract the amplitude and phase feature of GEI, research their recognition ability respectively, at last, fusion the two features in rank level to gait recognition...
Iris recognition has drawn a lot of attention since the mid-twentieth century. Among all biometric features, iris is known to possess a rich set of features. Different features have been used to perform iris recognition in the past. In this paper, two powerful sets of features are introduced to be used for iris recognition: scattering transform-based features and textural features. PCA is also applied...
This paper presents an iris segmentation algorithm. The proposed technique applies a histogram based method on the input eye image extracting a point within the pupil. The image is then intensity sampled over M equiangular radial scan line, generating M 1-dimensional signals. A Fuzzy multi-scale edge detection algorithm is then applied to each of the resulting radii signals, to accurately detect and...
The theme of work presented in this paper is a novel Iris recognition technique using partial energies of transformed iris image. To generate transformed iris images, various transforms like Cosine, Walsh, Haar, Kekre, Hartley transforms and their wavelet transforms are applied on the iris images. Feature vectors are then generated from these transformed Iris images using the concept of energy compaction...
Iris has a unique pattern that can be used in biometric recognition. To extract the features of the iris, it can be done based on the textural characteristics of the iris pattern. One method is a texture-based feature extraction using wavelet. To construct a wavelet type which matched for a signal, in this case two-dimensional signal from the iris image, the necessary steps are quite complex. In this...
Feature selection and feature optimization play an important role in iris recognition system. Iris recognition system provide the great security flexibility for authentication and identification of genuine and imposters users. In this paper we proposed an optimized feature selection process for iris image template creation. The feature extraction process is performed by wavelet transform function...
Iris recognition is the best breed authentication process among all the biometric traits. It is a biometric identification process that uses visual patterns of irides. Iris recognition has been acknowledged as one of the most accurate biometric modalities because of its high recognition rate. Here performance comparison among various proposed techniques of Iris Recognition using the fractional coefficients...
Due to the randomness of iris patterns, iris recognition systems are the most accurate, reliable and efficient way to recognize and identify people. However, the complex structure of an iris image results in the difficulty of iris representation especially for iris images of insufficient quality. In this paper we propose a new active contours models applied to segment iris images based on active contours...
Iris recognition is one of the most reliable biometric technologies. In order to improve the accuracy of iris recognition systems, and according to the variations in iris data, due to noises of the eyelids and eyelashes or inappropriate image acquisition environment, multiple iris images per person are enrolled. Therefore, these systems suffer from storage and computational overheads. This paper presents...
Iris Recognition is a reliable biometric identification system that uses fine textures of the Iris for person identification and verification. This paper presents a novel algorithm for accurate iris recognition using Ridgelet transform. In this work, the pupil and limbic boundaries are detected by using the equation of circle. Canny edge detection scheme is used for iris boundary detection. After...
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