کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6937919 | 1449890 | 2019 | 24 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Iris sensor identification in multi-camera environment
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Iris sensor identification in multi-camera environment Iris sensor identification in multi-camera environment](/preview/png/6937919.png)
چکیده انگلیسی
Large-scale identity projects such as the Unique Identification Authority of India (UIDAI) comprise of multiple individual organizations, which may use different sensors for enrolling the individuals while the data obtained at the time of verification can be collected from a different sensor. In such multi-camera scenario, it is imperative to perform image-based iris sensor identification. In this research, we propose an efficient algorithm to identify the sensor from which the iris image is captured. The proposed algorithm is the amalgamation of SVM fitness function based Bacteria Foraging (BF) feature selection and fusion of multiple features such as Block Image Statistical Measure (BISM), High Order Wavelet Entropy (HOWE), Texture Measure (TM), Single-level Multi-orientation Wavelet Texture (SlMoWT), and Image Quality Measures (IQM). The selected features are then given input to a supervised classification algorithm for iris sensor identification. The second contribution of this research is developing two sets of multisensor iris image databases that, in total, contain 6000 images with over 150 subjects. The results show that the proposed sensor classification algorithm is computationally very fast and yields an accuracy of over 99% on multiple databases.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Fusion - Volume 45, January 2019, Pages 333-345
Journal: Information Fusion - Volume 45, January 2019, Pages 333-345
نویسندگان
Akshay Agarwal, Rohit Keshari, Manya Wadhwa, Mansi Vijh, Chandani Parmar, Richa Singh, Mayank Vatsa,