z-logo
open-access-imgOpen Access
<title>Closed-boundary extraction of cancer cells using fuzzy edge linking technique</title>
Author(s) -
Bingo WingKuen Ling,
Kwong-Shun Tam
Publication year - 2002
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.467993
Subject(s) - fuzzy logic , enhanced data rates for gsm evolution , point (geometry) , edge detection , computer science , boundary (topology) , mathematics , algorithm , matrix (chemical analysis) , artificial intelligence , computer vision , image (mathematics) , image processing , geometry , mathematical analysis , materials science , composite material
Conference on Image Processing : Algorithms and Systems, San Jose, CA, January 2002Edge linking is an important task in a boundary extraction problem. In this paper, a fuzzy approach is proposed. The proposed system consists of a fuzzy edge detection module and a fuzzy edge linking module, respectively. The fuzzy edge detector gives a fuzzy membership matrix and an initial edge map. Once the initial edge map is obtained, the pairing of the start and end points of the edges as well as the linking of appropriate segments of edges in the map can be found using the fuzzy edge linking module, as follows: First, for any start point, the corresponding end point is found by searching for the shortest distance between the points. Second, for any start point as a reference point, we search for the greatest fuzzy membership value among its neighbors, and connect the reference point to that neighbor. Then with that neighbor as the new reference point, this step of searching is repeated until the end point is reached. After applying the above technique to all the pairs of start and end points, all the open boundaries will be connected. A simulation evaluation of the proposed technique was carried out on an image 'Cancer.' The simulation result shows an improvement on the outlines of the cancer cells. The proposed algorithm is simple and low cost, and can be implemented easily in some real-time applications.Department of Electronic and Information EngineeringRefereed conference pape

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom