Now showing items 1-7 of 7
| Abstract: | Iris Recognition is a highly efficient biometric identification system with great possibilities for future in the security systems area.Its robustness and unobtrusiveness, as opposed tomost of the currently deployed systems, make it a good candidate to replace most of thesecurity systems around. By making use of the distinctiveness of iris patterns, iris recognition systems obtain a unique mapping for each person. Identification of this person is possible by applying appropriate matching algorithm.In this paper, Daugman’s Rubber Sheet model is employed for irisnormalization and unwrapping, descriptive statistical analysis of different feature detection operators is performed, features extracted is encoded using Haar wavelets and for classification hammingdistance as a matching algorithm is used. The system was tested on the UBIRIS database. The edge detection algorithm, Canny, is found to be the best one to extract most of the iris texture. The success rate of feature detection using canny is 81%, False Accept Rate is 9% and False Reject Rate is 10%. |
| Description: | International Journal of Network Security & Its Applications (IJNSA), Vol.5, No.5, September 2013 |
| URI: | http://dyuthi.cusat.ac.in/purl/3904 |
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| EFFECTIVENESS O ... RIC RECOGNITION SYSTEM.pdf | (672.7Kb) |
| Abstract: | Treating e-mail filtering as a binary text classification problem, researchers have applied several statistical learning algorithms to email corpora with promising results. This paper examines the performance of a Naive Bayes classifier using different approaches to feature selection and tokenization on different email corpora |
| Description: | International Journal of Computer Science and Communication Vol. 3, No. 1, January-June 2012, pp. 81-84 |
| URI: | http://dyuthi.cusat.ac.in/purl/3915 |
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| FEATURE SELECTI ... TEXT OF SPAM FILTERING.pdf | (402.6Kb) |
| Abstract: | The paper investigates the feasibility of implementing an intelligent classifier for noise sources in the ocean, with the help of artificial neural networks, using higher order spectral features. Non-linear interactions between the component frequencies of the noise data can give rise to certain phase relations called Quadratic Phase Coupling (QPC), which cannot be characterized by power spectral analysis. However, bispectral analysis, which is a higher order estimation technique, can reveal the presence of such phase couplings and provide a measure to quantify such couplings. A feed forward neural network has been trained and validated with higher order spectral features |
| Description: | PROCEEDINGS OF SYMPOL 2009 |
| URI: | http://dyuthi.cusat.ac.in/purl/4682 |
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| Implementation ... seSources in the Ocean.pdf | (797.2Kb) |
| Abstract: | Biometrics is an efficient technology with great possibilities in the area of security system development for official and commercial applications. The biometrics has recently become a significant part of any efficient person authentication solution. The advantage of using biometric traits is that they cannot be stolen, shared or even forgotten. The thesis addresses one of the emerging topics in Authentication System, viz., the implementation of Improved Biometric Authentication System using Multimodal Cue Integration, as the operator assisted identification turns out to be tedious, laborious and time consuming. In order to derive the best performance for the authentication system, an appropriate feature selection criteria has been evolved. It has been seen that the selection of too many features lead to the deterioration in the authentication performance and efficiency. In the work reported in this thesis, various judiciously chosen components of the biometric traits and their feature vectors are used for realizing the newly proposed Biometric Authentication System using Multimodal Cue Integration. The feature vectors so generated from the noisy biometric traits is compared with the feature vectors available in the knowledge base and the most matching pattern is identified for the purpose of user authentication. In an attempt to improve the success rate of the Feature Vector based authentication system, the proposed system has been augmented with the user dependent weighted fusion technique. |
| URI: | http://dyuthi.cusat.ac.in/purl/5000 |
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| Dyuthi-T2069.pdf | (32.98Mb) |
| Abstract: | Biometrics has become important in security applications. In comparison with many other biometric features, iris recognition has very high recognition accuracy because it depends on iris which is located in a place that still stable throughout human life and the probability to find two identical iris's is close to zero. The identification system consists of several stages including segmentation stage which is the most serious and critical one. The current segmentation methods still have limitation in localizing the iris due to circular shape consideration of the pupil. In this research, Daugman method is done to investigate the segmentation techniques. Eyelid detection is another step that has been included in this study as a part of segmentation stage to localize the iris accurately and remove unwanted area that might be included. The obtained iris region is encoded using haar wavelets to construct the iris code, which contains the most discriminating feature in the iris pattern. Hamming distance is used for comparison of iris templates in the recognition stage. The dataset which is used for the study is UBIRIS database. A comparative study of different edge detector operator is performed. It is observed that canny operator is best suited to extract most of the edges to generate the iris code for comparison. Recognition rate of 89% and rejection rate of 95% is achieved |
| Description: | Computer Science & Information Technology (CS & IT) |
| URI: | http://dyuthi.cusat.ac.in/purl/3906 |
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| IRIS BIOMETRIC ... PLOYING CANNY OPERATOR.pdf | (667.4Kb) |
| Abstract: | Any automatically measurable, robust and distinctive physical characteristic or personal trait that can be used to identify an individual or verify the claimed identity of an individual, referred to as biometrics, has gained significant interest in the wake of heightened concerns about security and rapid advancements in networking, communication and mobility. Multimodal biometrics is expected to be ultra-secure and reliable, due to the presence of multiple and independent—verification clues. In this study, a multimodal biometric system utilising audio and facial signatures has been implemented and error analysis has been carried out. A total of one thousand face images and 250 sound tracks of 50 users are used for training the proposed system. To account for the attempts of the unregistered signatures data of 25 new users are tested. The short term spectral features were extracted from the sound data and Vector Quantization was done using K-means algorithm. Face images are identified based on Eigen face approach using Principal Component Analysis. The success rate of multimodal system using speech and face is higher when compared to individual unimodal recognition systems |
| Description: | International Journal of Computer Science and Communication Vol. 2, No. 1, January-June 2011, pp. 143-147 |
| URI: | http://dyuthi.cusat.ac.in/purl/3879 |
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| A PROTOTYPE FOR ... STEM BASED ON FACE AND.pdf | (501.0Kb) |
| Abstract: | This thesis addresses one of the emerging topics in Sonar Signal Processing.,viz.the implementation of a target classifier for the noise sources in the ocean, as the operator assisted classification turns out to be tedious,laborious and time consuming.In the work reported in this thesis,various judiciously chosen components of the feature vector are used for realizing the newly proposed Hierarchical Target Trimming Model.The performance of the proposed classifier has been compared with the Euclidean distance and Fuzzy K-Nearest Neighbour Model classifiers and is found to have better success rates.The procedures for generating the Target Feature Record or the Feature vector from the spectral,cepstral and bispectral features have also been suggested.The Feature vector ,so generated from the noise data waveform is compared with the feature vectors available in the knowledge base and the most matching pattern is identified,for the purpose of target classification.In an attempt to improve the success rate of the Feature Vector based classifier,the proposed system has been augmented with the HMM based Classifier.Institutions where both the classifier decisions disagree,a contention resolving mechanism built around the DUET algorithm has been suggested. |
| Description: | Departement of Electronics,Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/2481 |
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| Dyuthi-T0664.pdf | (12.19Mb) |
Now showing items 1-7 of 7
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