Sequential spatial reasoning in images based on pre-attention mechanisms and fuzzy attribute graphs

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.

• Type: Conference
• Year: 2008
• Where: ECAI
• Authors: Geoffroy Fouquier, Jamal Atif, Isabelle Bloch
• Keywords: Artificial Intelligence, ECAI 2008, Image Appearance Characteristics, Model-based Image Recognition, Spatial Relations