A fuzzy-watershed image segmentation of two-dimensional gel images-survey paper

Authors:
Shaheera Rashwan;Amany Sarhan;Talaat Faheem;Bayoumy Abdel Rahman Bayoumy
Affiliations:
Knowledge-Based Systems and Robotics Department, Informatics Research Institute, Mubarak City for Scientific Research, Alexandria, Egypt;Computer Science Department, Faculty of Engineering, Tanta University, Tanta, Egypt;Computer Science Department, Faculty of Engineering, Tanta University, Tanta, Egypt;Department of Computer-Based Applications, Institute of Informatics, Mubarak City for Scientific Research, Alexandria, Egypt
Venue:
ISCGAV'09 Proceedings of the 9th WSEAS international conference on Signal processing, computational geometry and artificial vision
Year:
2009

Citing 5
Cited 0

Image analysis for the biological sciences

Image analysis for the biological sciences
Pattern Recognition with Fuzzy Objective Function Algorithms

Pattern Recognition with Fuzzy Objective Function Algorithms
Fuzzy relations applied to minimize over segmentation in watershed algorithms

Pattern Recognition Letters
Convergence of max-arithmetic mean powers of a fuzzy matrix

Fuzzy Sets and Systems
Detection of buried landmines using the possibilistic correlation-dependent fusion methods

ISPRA'07 Proceedings of the 6th WSEAS International Conference on Signal Processing, Robotics and Automation

Quantified Score

Hi-index	0.00

Visualization

Abstract

2D gel electrophoresis (2DGE) plays an important role in proteomics. It can separate proteins effectively with their pI values and molecular weights. Proteomics researchers needed to identify interested protein spots by examining the gel. This is time-consuming and labor extensive. It is desired that the computer can analyze the proteins automatically by first detecting and quantifying the protein spots in the digitized 2DGE images. In our work, we will investigate the use of the watershed algorithm in segmenting the protein spots from the varying background. However, the watershed algorithm often produces an over-segmented result. So, we will introduce the notion of fuzzy relations to improve the segmentation result.