Automatic estimation of Artemia hatching rate using an object discrimination method SCOPUS KCI

Title
Automatic estimation of Artemia hatching rate using an object discrimination method
Author(s)
Kim, S.; Cho, H.-Y.
KIOST Author(s)
Kim, Sung(김성)Cho, Hong Yeon(조홍연)
Publication Year
2013
Abstract
Digital image processing is a process to analyze a large volume of information on digital images. In this study, Artemia hatching rate was measured by automatically classifying and counting cysts and larvae based on color imaging data from cyst hatching experiments using an image processing technique. The Artemia hatching rate estimation consists of a series of processes; a step to convert the scanned image data to a binary image data, a process to detect objects and to extract their shape information in the converted image data, an analysis step to choose an optimal discriminant function, and a step to recognize and classify the objects using the function. The function to classify Artemia cysts and larvae is optimally estimated based on the classification performance using the areas and the plan-form factors of the detected objects. The hatching rate using the image data obtained under the different experimental conditions was estimated in the range of 34-48%. It was shown that the maximum difference is about 19.7% and the average root-mean squared difference is about 10.9% as the difference between the results using an automatic counting (this study) and a manual counting were compared. This technique can be applied to biological specimen analysis using similar imaging information.
ISSN
1598-141X
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/3305
DOI
10.4217/OPR.2013.35.3.239
Bibliographic Citation
Ocean and Polar Research, v.35, no.3, pp.239 - 247, 2013
Keywords
Artemia; Cyst and larvae; Discriminant analysis; Hatching rate; Image analysis
Type
Article
Language
English
Document Type
Note
Related Researcher
Research Interests

Spawning ecology of fishes,Marine Environmental DNA Biomonitoring,어류산란생태,해양 eDNA 분석

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