Open AccessSaliency model based on a discrete centre‐surround
Author(s) -
Jin Zuolun,
Han Jing,
Zhang Yi,
Bai Lianfa
Publication year - 2015
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2014.4316
Subject(s) - saliency map , artificial intelligence , kadir–brady saliency detector , salient , contrast (vision) , prior probability , object (grammar) , filter (signal processing) , computer science , pattern recognition (psychology) , selection (genetic algorithm) , measure (data warehouse) , computer vision , mathematics , data mining , bayesian probability
A novel saliency model based on a discrete centre‐surround (C‐S) is proposed. By addressing the problem of filter scales selection commonly existing in the state‐of‐the‐art saliency methods, the contrast map, obtained by a discrete C‐S, can uniformly highlight salient objects. Furthermore, a saliency probability measure is derived from the combination of the discrete C‐S and saliency priors, which further enhances the object's saliency. Experimental results on a dataset containing 1000 test images with ground truths demonstrate that the proposed model clearly outperforms previous saliency models.