Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Computing | en_US |
| dc.creator | Lau, King-ho | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/2896 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Human facial image synthetic system | en_US |
| dcterms.abstract | Human facial image synthesis system allows the generation of near-photographic quality images of faces. It makes use of genetic algorithm to recombine the principal components of human faces images in response to user selection. This process is iterated through a number of generations, gradually getting closer to the target face. This purposed system is applicable for suspect identification, different to the traditional facial feature composition method, it describes the generated face images as a whole, and such that matches the way of human faces identification. It explains an image in terms of a set of model parameters, shapes and texture information. With the facial image database, we are able to synthesise a very close approximation to the target object by using image morphing technique. Therefore the process of facial image synthesis will become a combination and searching procedure, by using the Interactive genetic algorithm with user fitness rating, the prototype system will randomly generated face image and eventually converge to the user target. | en_US |
| dcterms.extent | 79 leaves : ill. ; 31 cm | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2006 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.LCSH | Human face recognition (Computer science) | en_US |
| dcterms.LCSH | Image processing | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b20809050.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 20.02 MB | Adobe PDF | View/Open |
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