Palm veins recognition and verification system

العناوين الأخرى

منظومة للتمييز و التحقيق من أوردة راحة اليد

مقدم أطروحة جامعية

Abbas, Asma Muhammad Jawad

مشرف أطروحة جامعية

Jurj, Luayy Adwar

أعضاء اللجنة

Dhannun, Ban Nadim
al-Abbudi, Bushra Qasim
Muhammad, Faysal Ghazi

الجامعة

جامعة بغداد

الكلية

كلية العلوم

القسم الأكاديمي

قسم علوم الحاسبات

دولة الجامعة

العراق

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2014

الملخص الإنجليزي

During the last years, hand vein patterns recognition is one of the most recent biometric technologies used for the identification/verification of individuals.

The vein trace is hard to damaged, changed or falsified since veins are internal to the human body.

In this work, a novel palm vein recognition and verification system is presented.

The system work flow passes through two main phases: (i) the enrollment phase and (ii) the recognition phase.

In the enrollment phase, the biometric system is trained to identity a specific person.

While, in the recognition phase, the system tries to identify who is the person (in case of identification) or to verify is the person who he/she claims to be (in case of verification).

The imaging quality and variability of the vein images acquired by the near-infrared (NIR) device present challenges to achieve high classification accuracy.

In the proposed system, the first two steps are image preprocessing and, then, the localization of veins grid (i.e., the region of interest, ROI).

So, the infrared palm image is entered into the preprocessing stage to improve the appearance of veins by applying a set of enhancement process, then, segmentation process is applied to isolate the veins grid area; a post-processing operation is, also applied to improve the shape of veins grid.

The palm vein feature extraction task is another challenging problem in the infrared hand palm recognition tasks.

In this research two set of features have been suggested to represent the veins grid attributes: (i) the spatial distribution of the local average of veins direction and (ii) the spatial energy distribution of wavelet sub-bands.

Each extracted feature list is assembled as a feature vector used to distinguish between palms belonging to different persons.

Euclidean Distance and City Block Distance measures have been used to make a decision in matching stage.

The system was tested over a database collected from 250 volunteers, where 24 images for the 2 palms of each person were collected.

In total, the database contains 6,000 images belonging to 500 different palms.

The achieved identification results indicated a high recognition rate of 99.95% when using the spatial distribution of the average of veins direction, and an excellent recognition rate of 100% when using spatial energy distribution of wavelet sub-bands.

The verification experimental results referred to a minimum error rate (equal error rate (EER)) equals 0.24%when using the first feature set; and equals 0.068% when using the second set.

These results indicate that the proposed method is perfect for palm-vein recognition tasks.

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

الموضوعات

• الأوعية الدموية
• معالجة البيانات

عدد الصفحات

101

قائمة المحتويات

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-605925