@Conference{Bea1985b,
author = {Beaulieu, Jean-Marie and Goldberg, Morris},
title = {Selection of Segment Similarity Measures for Hierarchical Picture Segmentation},
booktitle = {Proceedings Graphics Interface 1985},
volume = {},
publisher = {Canadian Information Processing Soc, Toronto, Ont, Can},
address = {Montreal, Que, Can},
issn = {07135424},
year = {1985},
month = {May 27-31},
pages = {179-186},
url = {},
doi = {},
abstract = {The problem of defining appropriate segment similarity measures for picture segmentation is examined. In agglomerative hierarchical segmentation, two segments are compared and merged if found similar. The proposed Hierarchical Step-Wise Optimization (HSWO) algorithm finds and then merges the two most similar segments, on a step-by-step basis. By considering picture segmentation as a piece-wise picture approximation problem, the similarity measure (or the step-wise criterion) is related to the overall approximation error. The measure then corresponds to the increase of the approximation error resulting from merging two segments. Similarity measures derived from constant approximations (zeroth order polynomials) and planar approximations (first order polynomials) are applied to a Landsat picture, and the results are presented.},
mypdf = {9},
keywords = {}
}