Segmenting focused objects in complex visual images

Abstract In this paper we aim at the segmentation of focused objects in complex visual images that contain foreground and background objects. The proposed approach is an unsupervised edge-based segmentation that relies on the measurement of defocus (blur) for object edges in an image. The amount of defocus at an edge pixel is evaluated using the moment-preserving principle. Edges of focused objects generate small amount of defocus, whereas edges of background objects yield large amount of defocus. Following an edge-linking procedure, the regions of focused objects can be bounded by closed boundaries. Experiments on a variety of visual images have shown correct segmentation, regardless of the complexity of foreground and background in images.

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