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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2074/323
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Full metadata record
| DC Field | Value | Language |
|---|
| contributor.author | Bajaj, Reena | - |
| contributor.author | Chaudhury, Santanu | - |
| date.accessioned | 2005-06-14T08:54:57Z | - |
| date.available | 2005-06-14T08:54:57Z | - |
| date.issued | 1997 | - |
| identifier.citation | Pattern Recognition, 30(1), 1-7 | en |
| identifier.uri | http://eprint.iitd.ac.in/dspace/handle/2074/323 | - |
| description.abstract | This paper is concerned with signature verification. Three different types of global features have been used for the classification of signatures. Feed-forward neural net based classifiers have been used. The features used for the classification are projection moments and upper and lower envelope based characteristics. Output of the three classifiers is combined using a connectionist scheme. Combination of these feature based classifiers for signature verification is the unique feature of this work. Experimental results show that
combination of the classifiers increases reliability of the recognition results. | en |
| format.extent | 243965 bytes | - |
| format.mimetype | application/pdf | - |
| language.iso | en | - |
| subject | Signature verification | en |
| subject | Projection moments | en |
| subject | Envelopes | en |
| subject | Neural net | en |
| subject | Combination of classifiers | en |
| title | Signature verification using multiple neural classifiers | en |
| type | Article | en |
| Appears in Collections: | Electrical Engineering
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Files in This Item:
| File |
Description |
Size | Format |
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| bajajsig97.pdf | | 238Kb | Adobe PDF | View/Open |
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