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the paper reports an attempt to improve performance and acceptance of the biometric system. a novel approach for iris recognition using fuzzy inference system (fis) is proposed by the paper. the approach has been implemented on iitd iris and casia iris v4. the experiments are done on various databases such as casia iris v1, casia iris v2, casia iris v3, casia iris v4, and iitd iris. the result analysis shows that the proposed scheme achieves higher accuracy and faster processing time. the presented scheme performs better than the existing methods like daugman’s model and daugman et al.’s model.

a hybrid iris recognition system is developed by the researchers to achieve the fastest face recognition system in the world. the proposed system combines two iris-recognition algorithms to achieve better recognition performance. the first algorithm is based on the principal component analysis (pca) and is proposed by tamhane et al. (2003). they have used 128 × 128 pixel image of the iris region to identify the iris. the second algorithm is based on the “fuzzy correlation coefficient” (fcc) and fuzzy logic. in their research, the authors have used the pca algorithm to extract the local features and the fuzzy logic for fusion. the result analysis shows that the proposed system outperforms the other state of the art systems. in the present study, the authors have shown that their system can achieve better performance in terms of accuracy and processing time.

iris recognition is used for authentication in various applications such as the banking, passport, and access control. irregularity in iris causes false accept (fa) and false reject (fr) errors. researchers have proposed several approaches to overcome this problem. a new approach has been proposed in this paper to overcome this problem. a multichannel support vector machine (msvm) classifier is used in the proposed system. experiments are conducted on casia database. the result analysis shows that the performance of the proposed system is much better than the existing systems. the proposed method is found to be effective for iris recognition in the presence of noise and nonuniform illumination.




the iris recognition system in this work has been developed using the open source software called “siril”. this software is an open source, cross-platform, full-featured, graphical, easy-to-use, highly customizable, and free iris recognition library [22]. this software is written in c++ language. this software provides a simple and easy to use library that requires no programming experience. the software provides the feature extraction, preprocessing, and iris matching functions for the iris recognition. its processing is very fast and does not consume a lot of memory, although iris sizes in this work are of about 64 bits. the principal goal of this work is to develop a research-grade iris recognition system that is fast and efficient. the conventional iris recognition systems can be classified into two groups: the first group is based on the physical iris pattern and the second is based on the features. the iris recognition systems are usually based on the physical pattern, as the patterns are unique to an individual. however, with the advancement in the technology, it is possible to use the extracted features of the iris images for recognition. in this work, we have developed an iris recognition system that is based on the features of the iris image. an iris image is divided into small blocks of similar size. a histogram is developed for each block and the features are extracted from the histograms. the iris recognition system is based on the histograms of the blocks of iris images. the iris recognition system can be used in standalone mode or be integrated with other software. the developed iris recognition system can be used for authentication of various applications, such as iris recognition in mobile phone and biometric security. the developed iris recognition system is less susceptible to the illumination changes than the conventional iris recognition system. the developed iris recognition system can be used to authenticate the iris images from the mobile devices. the proposed algorithm has been tested on the casia iris image database and the results show that the proposed algorithm performs better than the conventional algorithm. furthermore, the developed iris recognition system is tested on the iitd iris image database and the results show that the developed algorithm is superior to the conventional algorithm. 5ec8ef588b


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