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Radboud Repository
Article . 2005
Data sources: Radboud Repository
https://doi.org/10.1007/115524...
Part of book or chapter of book . 2005 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2017
Data sources: DBLP
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Parallel-Sequential Texture Analysis

Authors: Broek, E.L. van den; Rikxoort, E.M. van;

Parallel-Sequential Texture Analysis

Abstract

Color induced texture analysis is explored, using two texture analysis techniques: the co-occurrence matrix and the color correlogram as well as color histograms. Several quantization schemes for six color spaces and the human-based 11 color quantization scheme have been applied. The VisTex texture database was used as test bed. A new color induced texture analysis approach is introduced: the parallel-sequential approach; i.e., the color correlogram combined with the color histogram. This new approach was found to be highly successful (up to 96% correct classification). Moreover, the 11 color quantization scheme performed excellent (94% correct classification) and should, therefore, be incorporated for real-time image analysis. In general, the results emphasize the importance of the use of color for texture analysis and of color as global image feature. Moreover, it illustrates the complementary character of both features.

Country
Netherlands
Keywords

EWI-20950, HMI-VRG: Virtual Reality and Graphics, VisTex, correlogram, co-occurrence matrix, Color, Cognitive artificial intelligence, Pattern Recognition, IR-78922, HMI-MR: MULTIMEDIA RETRIEVAL, parallel-sequential, Texture

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    influence
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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!
3
Average
Top 10%
Average