Artificial neural networks-based face recognition

مقدم أطروحة جامعية

Hadhood, Sabah Finjan

مشرف أطروحة جامعية

Abbas, Iyad Ibrahim

الجامعة

الجامعة التكنولوجية

الكلية

-

القسم الأكاديمي

قسم الهندسة الكهربائية

دولة الجامعة

العراق

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2011

الملخص الإنجليزي

-Face recognition plays a major role in several applications, such as security, access to restricted areas, banking identity verification and recognition of wanted people at airport.

This work implements the face recognition system in two stages, the first stage is feature extraction stage and the second stage is the classification stage.

The feature extraction stage consists of Discrete Cosine Transform (DCT) and the Principle Component Analysis (PCA).

The DCT transform expresses the image by few coefficients and thus image compaction and hence simpler neural network structure .

The PCA is used for dimensionality reduction by finding patterns in data, and expressing the data in such a way to highlight their similarities and differences.

The second stage is the artificial neural network and it is used for input image classification by using the extracted features from the previous stage to find the similar image to the input image.

The research work implements a system that is capable of successful face recognition in the presence of image rotation, occlusion, and change in facial expression.

The proposed method is implemented using MATLAB 7.10.0.499 and Olivetti Research Laboratory (ORL) face images database, 40 face images are used for the training set and 8 images per person, 10 face images for test set with 2 images per person.

Three types of neural networks are used in this work as follows: 1.

Feed-forward Neural Network with Back-Propagation Algorithm.

2.

Probabilistic Neural Network (PNN).

3.

Pattern Recognition Neural Network.

The results obtained of face recognition system are good for the three types of neural networks and it is around 90%.

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

الموضوعات

• الشبكات العصبية(الحاسبات الإلكترونية)

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-304968