Bel1992

[Bel1992]
Post-segmentation classification of images containing small agricultural fields

Authors:Belaid Ait M, Geoffrey Edwards, A Jaton, KPB Thomson, Jean-Marie Beaulieu

Journal:Geocarto International

 1992, vol. 7, issue 3, p. 53–60

Publisher:Taylor & Francis

URL:https://www.tandfonline.com/doi/abs/10.1080/10106049209354380

DOI:10.1080/10106049209354380

Abstract:   This paper presents results from applying a hierarchical segmentation algorithm to two agricultural data sets characterised by small fields. Several new techniques were developed over the course of this project. These include a new supervised classification technique for identifying segments and the inclusion of other information derived from the segmentation process. In addition, a technique for including cartographic information to help structure the segmentation is also described. The results indicate that significant improvement in classification accuracy can be achieved. A number of problems which arise when working with segmentation data are also reported and discussed. These problems appear to be different enough from those encountered in pixel classifications to be worth describing in greater detail. The paper concludes with the lines of research being pursued to circumvent these problems and to further increase the fidelity of the segmentation results.

“Post-segmentation classification of images containing small agricultural fields,”
Belaid Ait M, Geoffrey Edwards, A Jaton, KPB Thomson, Jean-Marie Beaulieu,
Geocarto International, vol. 7, iss. 3, p. 53–60, 1992.
[Bibtex]

@Article{Bel1992,
author = {Belaid, M Ait and Edwards, Geoffrey and Jaton, A and Thomson, K P B and Beaulieu, Jean-Marie},
title = {Post-segmentation classification of images containing small agricultural fields},
journal = {Geocarto International},
volume = {7},
number = {3},
pages = {53--60},
year = {1992},
month = {},
abstract = {This paper presents results from applying a hierarchical segmentation algorithm to two agricultural data sets characterised by small fields. Several new techniques were developed over the course of this project. These include a new supervised classification technique for identifying segments and the inclusion of other information derived from the segmentation process. In addition, a technique for including cartographic information to help structure the segmentation is also described. The results indicate that significant improvement in classification accuracy can be achieved.
A number of problems which arise when working with segmentation data are also reported and discussed. These problems appear to be different enough from those encountered in pixel classifications to be worth describing in greater detail. The paper concludes with the lines of research being pursued to circumvent these problems and to further increase the fidelity of the segmentation results.},
publisher = {Taylor \& Francis},
url = {https://www.tandfonline.com/doi/abs/10.1080/10106049209354380},
issn = {},
doi = {10.1080/10106049209354380},
mypdf = {5},
address = {},
keywords = {}
}

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