{"product_id":"swarm-intelligence-for-iris-recognition-9780367627508","title":"Swarm Intelligence for Iris Recognition","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eIris recognition is a highly accurate biometric system, but external factors can cause errors. This book describes a new way of identifying and matching iris templates using nature-inspired algorithms, which is useful for students, practitioners, and industry practitioners. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 136 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 29 January 2024\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Taylor \u0026amp; Francis Ltd\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eIris recognition stands as one of the most accurate biometric systems employed, boasting remarkable precision. The accuracy of an iris recognition system is assessed through the False Reject Rate (FRR), which quantifies the authenticity of a user mistakenly rejected by the system due to alterations in iris characteristics, such as aging or health conditions, as well as external factors that impact iris image quality, like high noise rates. External factors, including technical faults, occlusions, and inadequate lighting during image acquisition, can lead to distorted iris images, resulting in incorrect rejections by the biometric system. To mitigate FRR, various techniques have been employed, including wavelets and Gabor filters, cascaded classifiers, ordinal measures, the integration of multiple biometric modalities, and the selection of distinctive iris features. However, despite these efforts, existing methods encountered challenges in accurately identifying the authenticity of users over extended matching processes, as the iris structure itself undergoes changes due to aging.\u003cbr\u003e\u003cbr\u003eIn fact, the iris possesses unique features that distinguish it among humans, including crypts, furrows, collarettes, pigment blotches, freckles, and pupils. Prior research focused on selecting specific iris features, yet their accuracy levels remained low.\u003cbr\u003e\u003cbr\u003eThis book presents a novel approach to identifying and matching iris templates using a nature-inspired algorithm. It offers a comprehensive overview of iris recognition, rooted in nature-inspired environment technology. This resource is invaluable for students enrolled in universities, polytechnics, community colleges, practitioners, and industry professionals seeking to delve into the realm of iris recognition.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 453g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 216 x 138 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9780367627508\u003c\/p\u003e","brand":"Zaheera Zainal Abidin","offers":[{"title":"Paperback \/ softback","offer_id":45179383742714,"sku":"9780367627508","price":23.79,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_6d43467f-1a72-427d-8083-730b75e872b4.jpg?v=1707752854","url":"https:\/\/shulphink.com\/products\/swarm-intelligence-for-iris-recognition-9780367627508","provider":"Shulph Ink","version":"1.0","type":"link"}