کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
536179 870478 2016 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Iris recognition based on sparse representation and k-nearest subspace with genetic algorithm
ترجمه فارسی عنوان
تشخیص عنبیه چشم بر اساس بازنمایی پراکنده و فضای فرعی نزدیکترین k با الگوریتم ژنتیک
کلمات کلیدی
تشخیص عنبیه چشم؛ سنجش فشرده؛ بازنمایی پراکنده ؛ فضای فرعی نزدیکترین k ؛ شاخص تجمع پراکنده؛ الگوریتم ژنتیک
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی


• Iris recognition model based on sparse representation using compressive sensing.
• k-nearest subspace approach used for short listing the classes to reduce the time.
• Classifiers: k-nearest distance, sector based and CSCI.
• Genetic algorithm is used to learn the weight of each of the classifier.
• Highly robust scheme with FAR almost zero.

Iris recognition has become an important tool for human authentication. An efficient and robust iris recognition model based on sparse representation using compressive sensing and k-nearest subspace (segments) has been proposed; k-nearest subspace approach is used for short listing the classes to reduce the time. The shortlisted candidates are divided into sectors and the sparse recognition is applied to each sector. Three classifiers: k-nearest distance classifier, Sector based classifier and Cumulative Sparse Concentration Index (CSCI) based classifiers have been used. An additive function based classifier combination scheme has been adopted in which each classifier is associated with a weight. Genetic algorithm is used to learn the weight of each of the classifier. Results obtained on different databases show that the scheme is highly robust with FAR almost zero.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 73, 1 April 2016, Pages 13–18
نویسندگان
, , , ,