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Performance Improvement in Gradient based Algorithm for the Estimation of Fingerprint Orientation Fields

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Meghna B. Patel, Satyen M. Parikh, Ashok R. Patel

Meghna B Patel, Satyen M Parikh and Ashok R Patel. Performance Improvement in Gradient based Algorithm for the Estimation of Fingerprint Orientation Fields. International Journal of Computer Applications 167(2):12-18, June 2017. BibTeX

	author = {Meghna B. Patel and Satyen M. Parikh and Ashok R. Patel},
	title = {Performance Improvement in Gradient based Algorithm for the Estimation of Fingerprint Orientation Fields},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {167},
	number = {2},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {12-18},
	numpages = {7},
	url = {},
	doi = {10.5120/ijca2017914176},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Accuracy of fingerprint recognition system is reliable for correct measurement of fingerprint features. Orientation estimation of fingerprint ridges is playing a vital role in image enhancement, segmentation, classification and recognition. The accurate estimation of ridge orientation improves the performance of minutiae extraction and matching algorithm. The noisy fingerprint does not contain the clear ridge structure, that’s why ridge orientation estimation is the toughest and challenging task in fingerprint image enhancement. Gradient-based orientation estimation algorithm is widely adopted and most popular method accepted in literature. This paper enhance the consistency level of ridge orientation after changing the range of output direction from [-PI/4, PI/4] to [0, PI] and remove the inconsistency. The implementation is done using java language and the experimental result is made on FVC2000 and FingerDOS databases. The outcome of enhanced new method for estimating ridge orientation give better performance than the existing gradient based approach.


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Fingerprint recognition, fingerprint enhancement, orientation estimation