A nonparametric approach for histogram segmentation

A nonparametric approach for histogram segmentation

In this work, we propose a method to segment a 1-D histogram without a priori assumptions about the underlying density function. Our approach considers a rigorous definition of an admissible segmentation, avoiding over and under segmentation problems. A fast algorithm leading to such a segmentation...

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Veröffentlicht in:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 16(2007), 1 vom: 29. Jan., Seite 253-61
1. Verfasser: Delon, Julie (VerfasserIn)
Weitere Verfasser: Desolneux, Agnès, Lisani, José-Luis, Petro, Ana Belén
Format: Aufsatz
Sprache:English
Veröffentlicht: 2007
Zugriff auf das übergeordnete Werk:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.
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520 |a In this work, we propose a method to segment a 1-D histogram without a priori assumptions about the underlying density function. Our approach considers a rigorous definition of an admissible segmentation, avoiding over and under segmentation problems. A fast algorithm leading to such a segmentation is proposed. The approach is tested both with synthetic and real data. An application to the segmentation of written documents is also presented. We shall see that this application requires the detection of very small histogram modes, which can be accurately detected with the proposed method 
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650 4 |a Research Support, U.S. Gov't, Non-P.H.S. 
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700 1 |a Lisani, José-Luis  |e verfasserin  |4 aut 
700 1 |a Petro, Ana Belén  |e verfasserin  |4 aut 
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