Proceedings Article10.5244/C.15.38
Evaluating image segmentation algorithms using monotonic hulls in fitness/cost space
Mark Everingham,Henk Muller,Barry T. Thomas +2 more
- 01 Sep 2001
- pp 1-10
TL;DR: This paper proposes a framework for quantitative evaluation of segmentation algorithms which it believes addresses shortcomings of previous approaches, and uses this framework to compare several state-of-the-art algorithms.
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Abstract: Image segmentation is the first stage of processing in many practical computer vision systems. While development of particular segmentation algorithms has attracted considerable research interest, relatively little work has been published on the subject of their evaluation. In this paper we propose a framework for quantitative evaluation of segmentation algorithms which we believe addresses shortcomings of previous approaches, and use this framework to compare several state-of-the-art algorithms.
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Citations
Assessing image segmentation quality – concepts, methods and application
Marco Neubert,Hendrik Herold,Gotthard Meinel +2 more
- 01 Jan 2008
TL;DR: This contribution gives an overview of existing methods for the evaluation of image segmentation quality and seven recent programs for remote sensing imagery are introduced and their results based on very high resolution IKONOS data are evaluated using an empirical discrepancy method.
142
Region growing with pulse-coupled neural networks: an alternative to seeded region growing
R.D. Stewart,I. Fermin,M. Opper +2 more
TL;DR: A novel region growing variant of the pulse-coupled neural network (PCNN) is demonstrated, which offers comparable performance to the SRG and is able to generate seed locations internally, opening the way to fully autonomous operation.
108
•Journal Article
Evaluating Image Segmentation Algorithms Using the Pareto Front
TL;DR: In this article, the Pareto front is used to evaluate image segmentation algorithms in multi-dimensional fitness spaces, in a manner similar to the use of receiver operating characteristic curves in binary classification problems.
73
Simulation of Ground-Truth Validation Data Via Physically- and Statistically-Based Warps
Ghassan Hamarneh,Preet Jassi,Lisa Tang +2 more
- 06 Sep 2008
TL;DR: An algorithm for the automatic generation of large databases of annotated images from a single reference dataset is developed, which uses variational and vibrational spatial deformations, nonlinear radiometric warps mimicking imaging nonhomogeneity, and additive random noise with different underlying distributions.
Full-reference objective quality metrics for video watermarking, video segmentation and 3D model watermarking
Elisa Drelie Gelasca
- 01 Jan 2005
TL;DR: New objective quality metrics that take into account how distortions are perceived, are proposed and three different signal processing systems are considered: video watermarking, video object segmentation and 3D modelsWatermarking.
31
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