Share
التعرف على الوجه بالاعتماد على الترميز الكسوري == Face Identification Based On Fractal Coding
Author name:
سعاد محسن صابر
Supervisor name:
جميلة حربي سعود العامري
General topic:
Computer Science
Specific topic:
Computer Science
Degree:
Master
University:
Mustansiriyah University - College Of Science - Department Of Computer
Language:
English
University location:
Baghdad
First pages:
28T839 - p.pdf
Abstract:
As technology is advancing, the requirements on face recognition which is one of biometric technologies are growing day by day. During the last years, numerous researchers have introduced various techniques and various algorithms for reliability and accuracy face patterns recognition.In this thesis Face Recognition System is presented. The framework is made of two parts : training phase and testing phase.There are two fundamental stages shared between the two phases of the system; the reading of the image stage and the face detection stage.After reading an image as bmp file, it is passesed to face detection stage which includes five steps; color transform, skin detection, noise removal, filling holse, and face localization. Four color spaces are used : RGB,YCbCr, HSV in the face detection stage and YIQ in the feature extraction stage. Also, medain filter is used to remove the noise, morphology operation is used to close the separated regions that appeared in face image, while connected component labeling (CCL) is used to determine the closed region .Two features are used in order to determine accurate face; the area of expected face and connected component operators ( Compactness, Solidity and Orientation ) . Next, two feature are extracted from the accurate face. This is achieved via FractalImage Coding(FIC) method with fixd block size partitioing ,which in turn is used to make a decision in the recognition stage of the system. These two features are the binary file which includes the face’s IFS code sets, dimensions and the coding parameters , and the second feature is fidelity criteria Peak Signal to Noise Ratio (PSNR). Face recognition system is tested over FEI face dataset and the recognition rate that has been achievedis 88% .i
