A multiresolution approach to computer verification of handwritten signatures.
| dc.contributor.author | Qi, Yingyong. | |
| dc.creator | Qi, Yingyong. | en_US |
| dc.date.accessioned | 2011-10-31T18:12:15Z | en |
| dc.date.available | 2011-10-31T18:12:15Z | en |
| dc.date.issued | 1993 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10150/186548 | en |
| dc.description.abstract | This dissertation presents procedures and results of works on computer signature verification. Two methods were developed and evaluated. First, verification was made using multi-resolution feature representation. This multi-resolution feature representation included global geometric characteristics and wavelet transformations of a signature image. A number of algorithms were developed to extract the global geometric features. A vector quantization classifier and a neural-network classifier were designed to use the multi-resolution representation for verification. Second, verification was made using a grid approach. In this approach, a signature image was divided by a grid and verification was made based on grid features that approximate local structures of a signature image. The grid feature comparison was made using dynamic programming procedures. Results indicated that both systems could detect free-handed forgeries accurately and could also monitor simulated forgeries with reasonable accuracy. | |
| dc.language.iso | en | en_US |
| dc.publisher | The University of Arizona. | en_US |
| dc.rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. | en_US |
| dc.subject | Dissertations, Academic. | en_US |
| dc.subject | Electrical engineering. | en_US |
| dc.subject | Computer science. | en_US |
| dc.title | A multiresolution approach to computer verification of handwritten signatures. | en_US |
| dc.type | text | en_US |
| dc.type | Dissertation-Reproduction (electronic) | en_US |
| dc.contributor.chair | Hunt, Bobby R. | en_US |
| dc.identifier.oclc | 721968125 | en_US |
| thesis.degree.grantor | University of Arizona | en_US |
| thesis.degree.level | doctoral | en_US |
| dc.contributor.committeemember | Strickland, Robin N. | en_US |
| dc.contributor.committeemember | Rodriguez, Jeffrey J. | en_US |
| dc.identifier.proquest | 9421755 | en_US |
| thesis.degree.discipline | Electrical and Computer Engineering | en_US |
| thesis.degree.discipline | Graduate College | en_US |
| thesis.degree.name | Ph.D. | en_US |
| refterms.dateFOA | 2018-06-15T19:38:15Z | |
| html.description.abstract | This dissertation presents procedures and results of works on computer signature verification. Two methods were developed and evaluated. First, verification was made using multi-resolution feature representation. This multi-resolution feature representation included global geometric characteristics and wavelet transformations of a signature image. A number of algorithms were developed to extract the global geometric features. A vector quantization classifier and a neural-network classifier were designed to use the multi-resolution representation for verification. Second, verification was made using a grid approach. In this approach, a signature image was divided by a grid and verification was made based on grid features that approximate local structures of a signature image. The grid feature comparison was made using dynamic programming procedures. Results indicated that both systems could detect free-handed forgeries accurately and could also monitor simulated forgeries with reasonable accuracy. |
