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Fixation-Based Visual Image Segmentation using the concept of Border-ownership

Manjusha Singh, Abhishek Misal

The reason behind the choice of segmenting an image based on a fixation point originates from the way humans perceive objects in their surroundings. Even when our eyes continuously fixate at different things in the scene to see/perceive them, most computer vision algorithms are yet to give any significance to fixation. It is believed that fixation (a part of visual attention) is the reason why human visual system works so well. This method proposes an approach where we do not segment the whole image in several regions and then reason on what these regions might be, but segment only the region which contains our fixation point. So in short segmenting an object from the scene implies finding a ��?fixation point��? and finding the contour of the object that encloses our point of interest. Border-ownership is an automated fixation strategy for finding interest points and it means - knowing the boundary of an object. Using the border ownership information, we automatically select fixation points inside all possible objects in the image and segment them. In this paper, some other ways are also briefly discussed which can be used to select fixation points such as Contrast-Saliency model and Symmetry-saliency model but we use Border-ownership method.