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Fingerprint Classification using KEVR Algorithm

International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 45 - Number 18
Year of Publication: 2012
Sudeep D. Thepade
Dimple Parekh
Vinita Murthi
Siddharth Mantri
Bhavin Shah

Sudeep D Thepade, Dimple Parekh, Vinita Murthi, Siddharth Mantri and Bhavin Shah. Article: Fingerprint Classification using KEVR Algorithm. International Journal of Computer Applications 45(18):5-7, May 2012. Full text available. BibTeX

	author = {Sudeep D. Thepade and Dimple Parekh and Vinita Murthi and Siddharth Mantri and Bhavin Shah},
	title = {Article: Fingerprint Classification using KEVR Algorithm},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {45},
	number = {18},
	pages = {5-7},
	month = {May},
	note = {Full text available}


Fingerprints offer an infallible means of personal identification. They are the most common and extensive form of biometric identification used at present. The use of fingerprint identification systems has become prevalent. The enormously growing size of fingerprint samples for identification systems has really become an issue these days. Fingerprint classification for the grouping of fingerprints which may further play as the pre processing of identification system has gained research momentum. The task of assigning the fingerprint to one of the considered classes is difficult. In this paper a novel technique based on Vector Quantization for fingerprint classification using Kekre's Error Vector Rotation (KEVR) is proposed. Also the comparison of the proposed method is done with the earlier presented fingerprint classification using KFCG. Here fingerprint classification is done on fingerprint images using KEVR codebook of size 8. The result obtained shows that this technique provides accuracy of 84% using KEVR codebook of size 8. Though this proposed method using KEVR takes little longer computations compared to existing method based on KFCG, it yields efficient results.


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