Development a zooplankton recognition method for dark field image

Author

Yajuan Wei ; Xinsheng Yu ; Yali Hu ; Dong Li

Author_Institution

Coll. of Inf. Sci. & Eng., Ocean Univ. of China, Qingdao, China

fYear

2012

fDate

16-18 Oct. 2012

Firstpage

861

Lastpage

865

Abstract

In this paper, an automated method for detection and recognition of marine plankton in the dark field images is proposed and evaluated. The features extracted with shape, invariant moment and texture information are used for the support vector machine (SVM) classifier. Three species of planktons were used for the performance evaluation and 86% classification accuracy was achieved. It is shown that the recognition accuracy based on watershed algorithm is better than that method based on adaptive threshold segmentation algorithm. The result shows this is a promising method for real-time application.

Keywords

ecology; feature extraction; geophysical image processing; image classification; image segmentation; image texture; microorganisms; real-time systems; shape recognition; support vector machines; SVM classifier; Zooplankton recognition method; adaptive threshold segmentation algorithm; automated method; dark field image; feature extraction; marine plankton detection; marine plankton recognition; performance evaluation; real-time application; shape invariant moment; support vector machine classifier; texture information; watershed algorithm-based recognition accuracy; Accuracy; Feature extraction; Image recognition; Image segmentation; Oceans; Support vector machines; Training; feature extraction; marine plankton; object segmentation; support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing (CISP), 2012 5th International Congress on

Conference_Location

Chongqing

Print_ISBN

978-1-4673-0965-3

Type

conf

DOI

10.1109/CISP.2012.6469941

Filename

6469941