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Proceedings Paper

Results of a hybrid segmentation method
Author(s): Ron P.H.M. Schoenmakers; Graeme G. Wilkinson; Theo E. Schouten
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Paper Abstract

A hybrid segmentation method has been developed integrating two segmentation methods, edge detection and region growing in order overcome weaknesses of either method. The segmentation method involves the following: (i) filtering, (ii) edge detection and following (iii) edge fragment linking, and (iv) region growing. In (ii) edge detection is carried out. The resulting edge magnitude values are thresholded and on the thresholded values a thinning operation is performed in order to create one pixel thick edges. In (iii) the resulting edge fragments are linked together where possible by detecting one pixel wide gaps between edge fragments. By connecting the edge fragments closed polygons are formed, dividing the image into a set of sub-images. Edge fragments not belonging to a closed polygon are pruned. In (iv) region growing is carried out within every polygon. Regions are not allowed to grow outside the polygons. The region growing method used is the best merge, which merges per merging scan over the image the pair with a lowest cost value. For merging remaining isolated pixels context rules are defined. Results of the segmentation method are shown for classification of a non-segmented Landsat-TM scene and its segmented counterpart by an artificial neural network. Moreover the use of the segmentation for filtering SAR imagery is indicated.

Paper Details

Date Published: 30 December 1994
PDF: 14 pages
Proc. SPIE 2315, Image and Signal Processing for Remote Sensing, (30 December 1994); doi: 10.1117/12.196708
Show Author Affiliations
Ron P.H.M. Schoenmakers, Telecom Italia (Italy)
Graeme G. Wilkinson, Institute for Remote Sensing Applications (United Kingdom)
Theo E. Schouten, Katholieke Univ. Nijmegen (Netherlands)

Published in SPIE Proceedings Vol. 2315:
Image and Signal Processing for Remote Sensing
Jacky Desachy, Editor(s)

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