مشاركة
وسيلة لاستراتيجية الاندماج الامثل في انظمة متعددة المقاييس الحيوية == An Approach to Optimal Fusion Strategy in Multibiometric Systems
اسم المؤلف:
نورة عمران علكم
اسم المشرف:
عامر صديق الملاح
الموضوع العام:
علوم الحاسبات
السنة:
2015
الموضوع الدقيق:
علوم الحاسبات
الدرجة:
ماجستير
الجامعة:
الجامعة المستنصرية - كلية العلوم - قسم الحاسوب
اللغة:
الانكليزية
مكان الجامعة:
بغداد
الصفحات الاولى:
28T849 - p.pdf
المستخلص:
Identification system has been widely covered by many researchers using different methods to reach to the desired goal with the best and accurate method. Most Identification systems which depend on a Single biometric have many restrictions such as noisy information, non universality, spoof attack and inadmissible rate of error. These restrictions will be solved by deploying multimodal biometric systems that has been proposed in this thesis. The multimodal biometric systems utilize two or more individual modalities, such as Fingerprint, Iris, Retina and Face. In this thesis , two biometrics, Fingerprint and Iris, are used as multibiometrics. The system consists of three main parts : First is Identification by fingerprint , the second is Identification by the iris, the third is the Fusion between the fingerprint and iris in one of the levels. A matching score and decision levels has been selected in this thesis .Wavelet packets transform is used to reduce the image size without losing the important information and two activation function wavelet networks as a features extractor and for fusion, score level and decision level are employed after biometric results for each trait founded separately. The fingerprint and iris images that are used for testing the system have been obtained from the from CASIA website and palacky university for (35) person which consist of (350) images, (175) fingerprint images and (175) iris images. The Error rate is shown by the results after testing the system is 8.6%. Two researches are published from this thesis that titled (Fingerprint and Iris Fusion for Identification),(Iris Identification Using Two Activation Function Wavelet Networks).
