Image Segmentation Using Gray‐Scale Morphology and Marker‐ControlledWatershed Transformation
Authors:
Open Access
- 5 January 2008
- journal article
- research article
- Published by Wiley in Discrete Dynamics in Nature and Society
- Vol. 2008 (1)
Abstract
Segmentation, a new method, for color, gray‐scale MR medical images, and aerial images, is proposed. The method is based on gray‐scale morphology. Edge detection algorithm includes function edge and marker‐controlled watershed segmentation. It features the simple algorithm implemented in MATLAB. The watershed segmentation has been proved to be a powerful and fast technique for both contour detection and region‐based segmentation. In principle, watershed segmentation depends on ridges to perform a proper segmentation, a property that is often fulfilled in contour detection where the boundaries of the objects are expressed as ridges. For region‐based segmentation, it is possible to convert the edges of the objects into ridges by calculating an edge map of the image. Watershed is normally implemented by region growing, based on a set of markers to avoid oversegmentation.Keywords
This publication has 6 references indexed in Scilit:
- Connectivity on Complete LatticesJournal of Mathematical Imaging and Vision, 1998
- A multiscale gradient algorithm for image segmentation using watersheldsPattern Recognition, 1997
- Theoretical aspects of morphological filters by reconstructionSignal Processing, 1995
- Connected operators and pyramids1993
- Morphological grayscale reconstruction in image analysis: applications and efficient algorithmsIEEE Transactions on Image Processing, 1993
- Watersheds in digital spaces: an efficient algorithm based on immersion simulationsIEEE Transactions on Pattern Analysis and Machine Intelligence, 1991