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Sclera Pattern Recognition for Identification

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Rohan Parab, Revathi A. S., Preeti Jha

Rohan Parab, Revathi A S. and Preeti Jha. Sclera Pattern Recognition for Identification. International Journal of Computer Applications 156(7):34-38, December 2016. BibTeX

	author = {Rohan Parab and Revathi A. S. and Preeti Jha},
	title = {Sclera Pattern Recognition for Identification},
	journal = {International Journal of Computer Applications},
	issue_date = {December 2016},
	volume = {156},
	number = {7},
	month = {Dec},
	year = {2016},
	issn = {0975-8887},
	pages = {34-38},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2016912470},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


In this paper a delineate the new human identification method is proposed: sclera recognition technique. Due to the uniqueness of the sclera pattern, it can be used as identification in place of code, fingerprint, face recognition and voice recognition. To distinguish different patterns, some tonal and illumination corrections are performed to get a clear sclera area without disturbing the vessel pattern structure[8]. This paper aims at developing a new method for sclera segmentation which works for both color as well as grayscale images. The blood vessel structure of sclera is different for different people and it lies in the region of the visible wavelengths, therefore it can be used for the human identification method (ID). To obtain shape and structure of a sclera vessel kernel functions are used in order to separate out the magnitude and phase plots. Gabor wavelet filter is a bi-dimensional Gaussian function which separates the R & G plane of the scanned image and due to its 2D nature, the B plane is difficult to plot as well as recognize (mathworks). Also lot of people has blue iris which is difficult to identify, hence plotting the graph of R and G only would be easy.


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Sclera Recognition, Gabor-wavelet filter, Kernel Function