Automatic segmentation of images with low depth of field (DOF) plays an important role in content-based multimedia applications. The proposed approach aims to separate the important objects (i.e., interest regions) of a given image from its defocused background in two stages. In stage one, image blocks are classified into object and background blocks using a novel cluster ensemble algorithm. By indicating the certain pixels (seeds) of the object and background blocks, a hard constraint is provided for the next stage of the approach. In stage two, a minimal graph cut is constructed using object and background seeds, which is based on the max-flow method. Experimental results for a wide range of busy-texture (i.e., noisy) and smooth regions demonstrate that the proposed approach provides better segmentation performance at higher speed compared with the state-of-the-art approaches.
|Title of host publication||Proceedings - 2012 IEEE International Symposium on Multimedia, ISM 2012|
|Number of pages||4|
|Publication status||Published - 1 Feb 2013|
|Event||14th IEEE International Symposium on Multimedia, ISM 2012 - Irvine, CA, United States|
Duration: 10 Dec 2012 → 12 Dec 2012
|Conference||14th IEEE International Symposium on Multimedia, ISM 2012|
|Period||10/12/12 → 12/12/12|