Title :
Shape-Based Classification of Environmental Microorganisms
Author :
Cong Yang ; Chen Li ; Tiebe, O. ; Shirahama, K. ; Grzegorzek, M.
Author_Institution :
Res. Group for Pattern Recognition, Univ. of Siegen, Siegen, Germany
Abstract :
Occurrence of certain environmental microorganisms and their species is a very informative indicator to evaluate environmental quality. Unfortunately, their manual recognition in microbiological laboratories is very time-consuming and expensive. Therefore, we work on an automatic method for shape-based classification of EMs in microscopic images. First, we segment the microorganisms from the background. Second, we describe their shapes by discriminative feature vectors. Third, we perform the EM classification using Support Vector Machines. The most important scientific contribution of this paper, in comparison to the state-of-the-art and to our previous publications in this field, is the introduction of a completely new and very robust 2D feature descriptor for EM shapes. Experimental results certify the effectiveness and practicability of our automatic EM classification system emphasising the benefits achieved with the new shape descriptor proposed in this work.
Keywords :
biology computing; feature extraction; image classification; microorganisms; support vector machines; 2D feature descriptor; EM classification; automatic EM classification system; discriminative feature vectors; environmental microorganisms; environmental quality evaluation; microbiological laboratory; microscopic images; shape descriptor; shape-based classification; support vector machines; Feature extraction; Image analysis; Image segmentation; Microorganisms; Microscopy; Shape; Support vector machines;
Conference_Titel :
Pattern Recognition (ICPR), 2014 22nd International Conference on
Conference_Location :
Stockholm
DOI :
10.1109/ICPR.2014.581