معلومات البحث الكاملة في مستودع بيانات الجامعة

عنوان البحث(Papers / Research Title)


Iris Recognition System Based on Texture Features


الناشر \ المحرر \ الكاتب (Author / Editor / Publisher)

 
سهاد احمد علي القره غولي

Citation Information


سهاد,احمد,علي,القره,غولي ,Iris Recognition System Based on Texture Features , Time 03/03/2017 18:20:23 : كلية العلوم للبنات

وصف الابستركت (Abstract)


Abstract— Nowadays iris recognition becomes one of the most common methods for identification like password, keys, etc. In this paper, a new iris recognition system based on texture has been proposed to recognize persons using low quality iris images. At first, the iris area is located, and then a new method for eyelash and eyelid detection is applied, the introduced method depends on making image statistical analysis, to isolate the unwanted eyelash/eyelid areas from the true iris area. For discrimination purpose a set of texture features determined from the Haar wavelet subbands is used. Here, the iris area is divided into overlapping blocks and the average energy of each Haar wavelet sub-band is determined to be used as a local feature indicator. Also, the new method depends on using a weighted overlap blocking algorithm to build the iris code. To evaluate the performance of proposed method, it was applied to identify a set of iris images taken from CASIA V4.0 (interval class) data set and CASIA V1 dataset. The test results indicated that the new method give good recognition rates (i.e., 100%) with small size of features vector for CASIA V4.0 and (99.2%) for CASIA V1 dataset.

الوصف الكامل (Full Abstract)

Abstract— Nowadays iris recognition becomes one of the most common methods for identification like password, keys, etc. In this paper, a new iris recognition system based on texture has been proposed to recognize persons using low quality iris images. At first, the iris area is located, and then a new method for eyelash and eyelid detection is applied, the introduced method depends on making image statistical analysis, to isolate the unwanted eyelash/eyelid areas from the true iris area. For discrimination purpose a set of texture features determined from the Haar wavelet subbands is used. Here, the iris area is divided into overlapping blocks and the average energy of each Haar wavelet sub-band is determined to be used as a local feature indicator. Also, the new method depends on using a weighted overlap blocking algorithm to build the iris code. To evaluate the performance of proposed method, it was applied to identify a set of iris images taken from CASIA V4.0 (interval class) data set and CASIA V1 dataset. The test results indicated that the new method give good recognition rates (i.e., 100%) with small size of features vector for CASIA V4.0 and (99.2%) for CASIA V1 dataset.

تحميل الملف المرفق Download Attached File

تحميل الملف من سيرفر شبكة جامعة بابل (Paper Link on Network Server) repository publications

البحث في الموقع

Authors, Titles, Abstracts

Full Text




خيارات العرض والخدمات


وصلات مرتبطة بهذا البحث