Val1988

[Val1988]
Quantitative Evaluation of Image Segmentation Techniques

Authors:Velarde Cesar, Jean-Marie Beaulieu

Conference:Canadian Conference on Electrical and Computer Engineering

 Montreal, Canads

 September 17-20, 1989, pp. 314-317

ISBN:0-9694170-0-4

Abstract:   The objective evaluation of picture segmentation techniques is an import ant and difficult topic. This paper presents an objective evaluation approach, based upon the comparison of the results of a given segmentation technique to either the ground truth, or to the results of another technique. Three performance criteria are defined : 1) the ability to extract the structure of the images, 2) the sensitivity to noise , and 3) the consistency between the results of two techniques. These performance criteria are measured for 4 segmentation techniques, over a set of artificial images. The results show that one of the techniques outperforms the others in retrieving the structure of the images. They also show that two techniques are less sensitive to noise than the others . Finally, we note that the four techniques produced essentially different picture partitions.

Quantitative Evaluation of Image Segmentation Techniques,
Velarde Cesar, Jean-Marie Beaulieu,
Canadian Conference on Electrical and Computer Engineering, Montreal, Canads, September 17-20, 1989, pp. 314-317.
[Bibtex]

@Conference{Val1988,
author = {Velarde, Cesar and Beaulieu, Jean-Marie},
editor = {},
title = {Quantitative Evaluation of Image Segmentation Techniques},
booktitle = {Canadian Conference on Electrical and Computer Engineering},
volume = {},
publisher = {},
url = {},
isbn = {0-9694170-0-4},
doi = {},
address = {Montreal, Canads},
pages = {314-317},
year = {1989},
month = {September 17-20},
abstract = {The objective evaluation of picture segmentation techniques is an import ant and difficult topic. This paper presents an objective evaluation approach, based upon the comparison of the results of a given segmentation technique to either the ground truth, or to the results of another technique. Three performance criteria are defined : 1) the ability to extract the structure of the images, 2) the sensitivity to noise , and 3) the consistency between the results of two techniques. These performance criteria are measured for 4 segmentation techniques, over a set of artificial images. The results show that one of the techniques outperforms the others in retrieving the structure of the images. They also show that two techniques are less sensitive to noise than the others . Finally, we note that the four techniques produced essentially different picture partitions.},
mypdf = {9},
keywords = {}
}

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