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The Novle Strategy for the Recognition and Classification of the Red Blood Cell in Low Quality Form Images

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 269)

Abstract

In this paper, we describe a novle strategy for the recognition and classification of the red blood cell (RBC) in low quality form images. At present, the classification of red blood cells has become one of the routine inspection of hospital, the inspection result has the very vital significance for the clinical diagnosis. Under the microscope, however, the work is very time consuming, and the different person have different classification error. Therefore, people are trying to use computer technology to help people eye brain system to complete the work and in this area of research is still ongoing. This paper proposes a method can be better applied to the automatic identification of red blood cells, and the experimental results show that the research results can be applied to clinical diagnosis, reduce the labor intensity of professionals and is conducive to the doctor’s diagnosis. The new cell recognition algorithm improves accuracy while the speed is suitable for practical applications. The Smear of this experiment is made by conventional method and use an Olympus camera magnified 800 times of cells on the film imaging, the grey scale 256.

Keywords

RBC Pattern recognition Support vector machines (SVM) Decision tree Edge detection 

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyShandong UniversityJinanChina

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