Hybrid of Mean-shift and median-cut algorithm for fish segmentation

Author

Mokti, Mohammad Nordin ; Salam, Rosalina Abdul

Author_Institution

Sch. of Comput. Sci., Univ. Sains Malaysia, Minden

fYear

2008

fDate

1-3 Dec. 2008

Firstpage

1

Lastpage

5

Abstract

In this paper, a hybrid of mean-shift and median-cut algorithm was introduced to perform segmentation on color images. Firstly, the image pre-processing technique was applied to enhance the image before changing the color space to LUV color space. Then mean-shift segmentation was introduced. However, some region has no semantic meaning since the mean-shift algorithm performed low level segmentation. To overcome this problem, median-cut algorithm was proposed to join the gap left by the mean-shift. The hybrid of the two methods has improved the contour extraction for further processing.

Keywords

edge detection; feature extraction; image colour analysis; image segmentation; object recognition; zoology; LUV color space; biological species identification system; color image segmentation; contour extraction; edge detection; fish segmentation; image pre-processing technique; mean-shift algorithm; median-cut algorithm; Algorithm design and analysis; Binary search trees; Color; Computerized monitoring; Image edge detection; Image recognition; Image segmentation; Insects; Marine animals; Testing; Color image Segmentation; edge detection; k-Means segmentation; mean shift; median-cut;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronic Design, 2008. ICED 2008. International Conference on

Conference_Location

Penang

Print_ISBN

978-1-4244-2315-6

Electronic_ISBN

978-1-4244-2315-6

Type

conf

DOI

10.1109/ICED.2008.4786645

Filename

4786645