|dc.contributor.author||Poon, Bruce Siu-Lung||-|
|dc.description.abstract||The technology of human face recognition is now mature enough to be widely used in security by law enforcement agencies for dealing with criminal activities, government agencies for border control as well as government organizations and private enterprises for access control. However, there are still a lot of room for improvement.
In this thesis, we study strategies to improve the recognition accuracy. Two proposed schemes, Principal Component Analysis (PCA) and Gabor wavelet, for human face recognition are discussed and the implementations of sub-modules in each scheme are introduced.
In principal component analysis based human face recognition, we started from the basic method by first identified and developed the major testing criteria. Once the major testing criteria were developed, we analyzed those criteria which had significant impacts on the accuracy of recognition. More face databases were used in order to positively identify those criteria. Distorted images with poor illumination at the background had been identified as one of the major impacts on the accuracy of recognition. We then further investigated on this criteria and found ways to improve the results of recognition.
In Gabor wavelet based human face recognition, we first examined the classification capability of 40 different basic Gabor phase representations. We utilized those Gabor features from facial images, tested on the selected distorted images and compared the results and findings with the principle component analysis based human face recognition.||en_AU|
|dc.publisher||University of Sydney||en_AU|
|dc.publisher||Faculty of Engineering and Information Technologies||en_AU|
|dc.publisher||School of Electrical and Information Engineering||en_AU|
|dc.rights||The author retains copyright of this thesis. It may only be used for the purposes of research and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission.||en_AU|
|dc.title||Recognition of human faces in distorted images based on principal component analysis and gabor wavelets||en_AU|
|dc.type.pubtype||Doctor of Philosophy Ph.D.||en_AU|
|dc.description.disclaimer||Access is restricted to staff and students of the University of Sydney . UniKey credentials are required. Non university access may be obtained by visiting the University of Sydney Library.||en_AU|
|Appears in Collections:||Sydney Digital Theses (University of Sydney Access only)|