Academic Journal
EURASIP Journal on Applied Signal Processing 2003:9, 890–901 c ○ 2003 Hindawi Publishing Corporation An Efficient Feature Extraction Method with Pseudo-Zernike Moment in RBF Neural Network-Based Human Face Recognition System
| العنوان: | EURASIP Journal on Applied Signal Processing 2003:9, 890–901 c ○ 2003 Hindawi Publishing Corporation An Efficient Feature Extraction Method with Pseudo-Zernike Moment in RBF Neural Network-Based Human Face Recognition System |
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| المؤلفون: | Javad Haddadnia, Majid Ahmadi, Karim Faez |
| المساهمون: | The Pennsylvania State University CiteSeerX Archives |
| المصدر: | http://asp.eurasipjournals.com/content/pdf/1687-6180-2003-267692.pdf. |
| سنة النشر: | 2003 |
| المجموعة: | CiteSeerX |
| مصطلحات موضوعية: | human face recognition, face localization, moment invariant, pseudo-Zernike moment, RBF neural network |
| الوصف: | This paper introduces a novel method for the recognition of human faces in digital images using a new feature extraction method that combines the global and local information in frontal view of facial images. Radial basis function (RBF) neural network with a hybrid learning algorithm (HLA) has been used as a classifier. The proposed feature extraction method includes human face localization derived from the shape information. An efficient distance measure as facial candidate threshold (FCT) is defined to distinguish between face and nonface images. Pseudo-Zernike moment invariant (PZMI) with an efficient method for selecting moment order has been used. A newly defined parameter named axis correction ratio (ACR) of images for disregarding irrelevant information of face images is introduced. In this paper, the effect of these parameters in disregarding irrelevant information in recognition rate improvement is studied. Also we evaluate the effectofordersofPZMIinrecognitionrateoftheproposed technique as well as RBF neural network learning speed. Simulation results on the face database of Olivetti Research Laboratory (ORL) indicate that the proposed method for human face recognition yielded a recognition rate of 99.3%. |
| نوع الوثيقة: | text |
| وصف الملف: | application/pdf |
| اللغة: | English |
| Relation: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.396.7980; http://asp.eurasipjournals.com/content/pdf/1687-6180-2003-267692.pdf |
| الاتاحة: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.396.7980 http://asp.eurasipjournals.com/content/pdf/1687-6180-2003-267692.pdf |
| Rights: | Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
| رقم الانضمام: | edsbas.38D5C0F5 |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |