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Effective Information and Contrast Based Saliency Detection

  • Aditi KapoorEmail author
  • K. K. Biswas
  • M. Hanmandlu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9475)

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.

Keywords

Membership Function Salient Object Conditional Random Field Saliency Detection Connected Component Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Amar Nath and Shashi Khosla School of Information TechnologyIndian Institute of Technology Delhi Hauz KhasNew DelhiIndia
  2. 2.Department of Computer Science and EngineeringIndian Institute of Technology Delhi Hauz KhasNew DelhiIndia
  3. 3.Department of Electrical EngineeringIndian Institute of Technology Delhi Hauz KhasNew DelhiIndia

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