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Proceedings Paper

Segmentation evaluation using ultimate measurement accuracy
Author(s): Yujin Zhang; Jan J. Gerbrands
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Paper Abstract

As a wide range of segmentation techniques have been developed in the last two decades, the evaluation and comparison of segmentation techniques becomes indispensable. In this paper, after a thorough review of previous work, we present a general approach for evaluation and comparison of segmentation techniques. More specifically, under this general framework, we propose to use the ultimate measurement accuracy to assess the performance of different algorithms. In image analysis, the ultimate goals of segmentation and other processing are often to obtain measurements of the object features in the image. Therefore, the accuracy of those ultimate measurements over segmented images would be a good index revealing the performance of segmentation techniques. We feel this measure is of much greater importance than, e.g., error probabilities on pixel labeling, or even specially developed figure of merit. There exist many features describing the properties of the objects in the image. Some of them are discussed here and their applicability and performance in the context of segmentation evaluation are studied. Based on experimental results, we provide some useful guidelines for choosing specific measurements for different evaluation situations and for selecting adequate techniques in particular segmentation applications.

Paper Details

Date Published: 19 May 1992
PDF: 12 pages
Proc. SPIE 1657, Image Processing Algorithms and Techniques III, (19 May 1992); doi: 10.1117/12.58350
Show Author Affiliations
Yujin Zhang, Delft Univ. of Technology (Netherlands)
Jan J. Gerbrands, Delft Univ. of Technology (Netherlands)

Published in SPIE Proceedings Vol. 1657:
Image Processing Algorithms and Techniques III
James R. Sullivan; Benjamin M. Dawson; Majid Rabbani, Editor(s)

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