A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy Relative Position Between Objects in Image Processing: A Morphological Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
2006 Special Issue: Modeling attention to salient proto-objects
Neural Networks
Fuzzy spatial relationships for image processing and interpretation: a review
Image and Vision Computing
Local reasoning in fuzzy attribute graphs for optimizing sequential segmentation
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
Fuzzy and Bipolar Mathematical Morphology, Applications in Spatial Reasoning
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
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Spatial relations play a crucial role in model-based image recognition and interpretation due to their stability compared to many other image appearance characteristics, and graphs are well adapted to represent such information. Sequential methods for knowledgebased recognition of structures require to define in which order the structures have to be recognized, which can be expressed as the optimization of a path in the representation graph. We propose to integrate pre-attention mechanisms in the optimization criterion, in the form of a saliency map, by reasoning on the saliency of spatial area defined by spatial relations. Such mechanisms extract knowledge from an image without object recognition in advance and do not require any a priori knowledge on the image. Therefore, pre-attentional mechanisms provide useful knowledge for object segmentation and recognition. The derived algorithms are applied on brain image understanding.