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Natural Image Segmentation Using the CIELab Space

Authors: Geovanni Hernandez-Gomez; Raúl Enrique Sánchez-Yáñez; Víctor Ayala-Ramírez; Fernando E. Correa-Tome;

Natural Image Segmentation Using the CIELab Space

Abstract

In this work, we have tested a color based segmentation approach that uses the CIELab color space. We use a color reduction approach where the dominant color database is obtained from the analysis of the entire Berkeley natural image database. After experiments using single color components and all their possible combinations as the segmentation basis, we have found that ab is the best color component combination for the segmentation task. F measures and Precision Recall graphs are used as the evidence for this conclusion.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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