Automatic Recognition of Rodent Species based on Mathematical Morphological Characterization of Skull
Bibi Ayesha.H.Patel1, K.Indira2
1Bibi Ayesha Patel, Department of Electronics and Communication, MSRIT, Bangalore India.
2Dr. K Indira, Professor Department of EC, MSRIT Bangalore, India.
Manuscript received on March 22, 2014. | Revised Manuscript received on April 19, 2014. | Manuscript published on April 30, 2014. | PP: 385-387 | Volume-3, Issue-4, April 2014. | Retrieval Number: D3035043414/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Morphological image processing is a collection of non-linear operations related to the shape or morphology of features in an image. Digital image processing technique applied to extract morphological features of skull image taken from optical camera. Based on the prominent nine extracted morphological features of rodent species, the closed form univariate two-factor analysis is derived. These two factor analysis is used for real time auto-recognition uniqueness of rodent species such as Meriones unguiculatus, Microtus brandti and Rattus norvegicus. The same two-factor auto-recognition analysis is used over x-ray image of rodent’s skull as well as other rodent species like squirrel. The considered morphological features are short axis(X1), perimeter(X2), eccentricity(X3), sphericity(X4), bump area(X5), paraxial area of enclosing rectangle(X6), hu1(X7), hu2(X8), hu3(X9).
Keywords: Morphological image processing, Humoments, Rodent species.