Factorization-based segmentation Python implementation

This is a Python implementation of the factorization-based segmentation algorithm, which fast segments textured images. The algorithm is described in

J. Yuan, D. L. Wang, and A. M. Cheriyadat. Factorization-based texture segmentation. IEEE Transactions on Image Processing, 2015.

Here is a brief introduction of the algorithm. Here is an explanation of computing local histograms based on integral histograms.

There is also a MATLAB implementation. The results from two implementations are similar. Local spectral histogram computation is coded using pure matrix operations, and thus achieves a speed comparable to the mex c code in MATLAB implementation.

Prerequisites

Python 2.7

Numpy

Scipy

Scikit-image

Usage

To try the code, run

python FctSeg.py

This verison implements the complete algorithm, which segments an image in a fully automatic fashion.

To try the version with given seeds, run

python FctSeg_seed.py

Each seed is a pixel location inside one type of texture. Note that this version represents the basic form of the algorithm and does not include nonnegativity constraint.

Three test images are provided.