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Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 194953, 20 pages
http://dx.doi.org/10.1155/2012/194953
Research Article

A Combined Approach on RBC Image Segmentation through Shape Feature Extraction

1College of Computer Science, Chongqing University, Chongqing 400030, China
2Department of Science and Technology, Chongqing University of Arts and Sciences, Chongqing 402160, China

Received 11 November 2011; Accepted 26 December 2011

Academic Editor: Ming Li

Copyright © 2012 Ruihu Wang and Bin Fang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The classification of erythrocyte plays an important role in clinic diagnosis. In terms of the fact that the shape deformability of red blood cell brings more difficulty in detecting and recognize for operating automatically, we believed that the recovered 3D shape surface feature would give more information than traditional 2D intensity image processing methods. This paper proposed a combined approach for complex surface segmentation of red blood cell based on shape-from-shading technique and multiscale surface fitting. By means of the image irradiance equation under SEM imaging condition, the 3D height field could be recovered from the varied shading. Afterwards the depth maps of each point on the surfaces were applied to calculate Gaussian curvature and mean curvature, which were used to produce surface-type label image. Accordingly the surface was segmented into different parts through multiscale bivariate polynomials function fitting. The experimental results showed that this approach was easily implemented and promising.