
A Novel Salient Region Detection Method Based on Hierarchical Spatial Information
Author(s) -
Liu Shuo,
Ding Wenrui,
Li Hongguang,
Li Yingting
Publication year - 2017
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2017.01.027
Subject(s) - salient , computer science , pattern recognition (psychology) , artificial intelligence , data mining
Different patterns in one object will cause unequal saliency degree which makes it hard to highlight the object region uniformly. We propose a salient region detection method which mainly includes image abstraction, saliency calculation and integration. Under the detection framework, the hierarchical spatial information is introduced to improve the performance. The image abstraction with “pixel level” spatial information is applied to capture some meaningful elements. The local contrast is calculated with the “element level” spatial information. The “object level” spatial information is represented as compactness and background possibility, which further help to better pop out the object region and suppress the background. The results show that our method has a good performance even though the object consists of complex patterns.