Algorithms efficient segmentation non ideal par rapaka satish (11 résultats)

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Taschenbuch. Etat : Neu. Algorithms for Efficient Segmentation of Non-ideal Iris Images | Optimization Based Segmentation Techniques For Iris Recognition System | Satish Rapaka (u. a.) | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207997121 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 140 pp. Englisch.

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Among the biometric technologies available, the iris biometric technology is the most accurate modality, because iris complex random patterns are unique and stable, they do not change throughout a person's lifetime. The Iris recognition is based on the fact that the human iris contains unique features and even genetically identical individuals have entirely independent iris textures. Iris segmentation is an essential step because the actual discriminating information will be present within the iris patterns. Therefore, it is plausible that the initial step in implementing an iris recognition system is separating the iris from irrelevant parts of an eye image, which are of no importance. A pre- segmentation using Otsu's multilevel thresholding and variants of fuzzy c-means (FCM) based on IPSO (improved PSO) and IDSA (improved differential search algorithm) has not been investigated in the literature. The recognition accuracy is affected by noise artefacts that are included during the capturing of iris images. This encourages to effective implementation and accurate pre-segmentation in the recognition framework.…

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Among the biometric technologies available, the iris biometric technology is the most accurate modality, because iris complex random patterns are unique and stable, they do not change throughout a person's lifetime. The Iris recognition is based on the fact that the human iris contains unique features and even genetically identical individuals have entirely independent iris textures. Iris segmentation is an essential step because the actual discriminating information will be present within the iris patterns. Therefore, it is plausible that the initial step in implementing an iris recognition system is separating the iris from irrelevant parts of an eye image, which are of no importance. A pre- segmentation using Otsu's multilevel thresholding and variants of fuzzy c-means (FCM) based on IPSO (improved PSO) and IDSA (improved differential search algorithm) has not been investigated in the literature. The recognition accuracy is affected by noise artefacts that are included during the capturing of iris images. This encourages to effective implementation and accurate pre-segmentation in the recognition framework.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch.…