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DC Field | Value | Language |
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dc.contributor.advisor | Mitra, Suman K. | |
dc.contributor.author | Athale, Suprita | |
dc.date.accessioned | 2017-06-10T14:36:53Z | |
dc.date.available | 2017-06-10T14:36:53Z | |
dc.date.issued | 2004 | |
dc.identifier.citation | Athale, Suprita (2004). Fractal based approach for face recognition. Dhirubhai Ambani Institute of Information and Communication Technology, 44 p. (Acc.No: T00026) | |
dc.identifier.uri | http://drsr.daiict.ac.in/handle/123456789/63 | |
dc.description.abstract | An automated face recognition system is proposed in this dissertation. The system efficiently recognizes a candidate (test) image using the interdependence of the pixel that arises from the fractal compression of the image. The interdependence of the pixels is inherent within the fractal code in the form of chain of pixels. The mechanism of capturing these chains from the fractal codes is called pixel chaining. The present face recognition system tries to match pixel chains of the candidate image with that of the images present in the database. The work domain of the system is fractal codes but not the images. This leads to an advantage towards handling large database of face images. <p/> <p/>The system performance is found to be very satisfactory with the recognition rate of 98.4%. A minor improvement in the performance of the system over a few existing methods has been observed. | |
dc.publisher | Dhirubhai Ambani Institute of Information and Communication Technology | |
dc.subject | Computer vision | |
dc.subject | Face recognition | |
dc.subject | Fractals | |
dc.subject | Image compression | |
dc.subject | Pattern recognition systems | |
dc.subject | VLSI systems | |
dc.classification.ddc | 006.4 ATH | |
dc.title | Fractal based approach for face recognition | |
dc.type | Dissertation | |
dc.degree | M. Tech | |
dc.student.id | 200211035 | |
dc.accession.number | T00026 | |
Appears in Collections: | M Tech Dissertations |
Files in This Item:
File | Description | Size | Format | |
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200211035.pdf Restricted Access | 960.88 kB | Adobe PDF | View/Open Request a copy |
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