Precise object cutout from images

ABSTRACT

In this paper we propose a novel approach to the problem of interactive foreground/background segmentation in images. With user provided strokes which indicate foreground and background seeds, we estimate two Gaussian mixture models, one for foreground and the other for background, and define two quantities to measure the initial probabilities of each pixel belonging to the foreground and the background respectively. An optimization function constructed based on the quantities and the boundary and coherent region information is proposed to solve the segmentation problem. By relaxing the hard binary segmentation to a soft labelling problem in the continuous domain, a closed form global optimal solution can be achieved, which directly results in the final binary segmentation output. Experimental results demonstrate the excellent performance of our algorithm.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.6 Segmentation
          Subjects: Region growing, partitioning

Additional Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.6 Segmentation
          Subjects: Relaxation

General Terms:
Algorithms, Experimentation

Keywords:
interactive image segmentation, label relaxation, optimization