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Erschienen in:
Hybrid Example-Based Single Image Super-Resolution Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

Effective Information and Contrast Based Saliency Detection

verfasst von : Aditi Kapoor, K. K. Biswas, M. Hanmandlu

Erschienen in: Advances in Visual Computing

Verlag: Springer International Publishing

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Abstract

Human attention tends to get focused on the most prominent objects in a scene which are different from the background. These are termed as salient objects. The human brain perceives an object of salient type based on its difference with the surroundings in terms of color and texture. There have been many color based approaches in the past for salient object detection. In this paper, we augment information set features with color features and detect the final single salient object using a set of color, size and location based features. The information set features result from representing the uncertainty in the color and illumination components. To locate the salient parts of the image, we make use of the entropy to find the uncertainties in the color and luminance components of the image. Extensive comparisons with the state-of-the-art methods in terms of precision, recall and F-Measure are made on two different publicly available datasets to prove the effectiveness of this approach.

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Vorheriges Kapitel Segmentation of Building Facade Towers
Nächstes Kapitel Edge Based Segmentation of Left and Right Ventricles Using Two Distance Regularized Level Sets
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Metadaten
Titel
Effective Information and Contrast Based Saliency Detection
verfasst von
Aditi Kapoor
K. K. Biswas
M. Hanmandlu
Copyright-Jahr
2015
Buch
Advances in Visual Computing

Print ISBN: 978-3-319-27862-9

Electronic ISBN: 978-3-319-27863-6

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-27863-6_18

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