  Color image segmentation is an important topic in the image processing field.
MRF-MAP is often adopted in the unsupervised segmentation methods, but their
performance are far behind recent interactive segmentation tools supervised by
user inputs. Furthermore, the existing related unsupervised methods also suffer
from the low efficiency, and high risk of being trapped in the local optima,
because MRF-MAP is currently solved by iterative frameworks with inaccurate
initial color distribution models. To address these problems, the letter
designs an efficient method to calculate the energy functions approximately in
the non-iteration style, and proposes a new binary segmentation algorithm based
on the slightly tuned Lanczos eigensolver. The experiments demonstrate that the
new algorithm achieves competitive performance compared with two state-of-art
segmentation methods.
