Texture Based Segmentation using Statistical Properties for Mammographic Images

Segmentation is very basic and important step in computer vision and image processing. For medical images specifically accuracy is much more important than the computational complexity and thus time required by process. But as volume of data of patients goes on increasing then it becomes necessary to think about the processing time along with accuracy. Here in this paper, new algorithm is proposed for texture based segmentation using statistical properties. For that probability of each intensity value of image is calculated directly and image is formed by replacing intensity by its probability . Variance is calculated in three different ways to extract the texture features of the mammographic images. These results of proposed algorithm are compared with well known GLCM and Watershed algorithm.

@article{Kekre2010,
  title     = {Texture Based Segmentation using Statistical Properties for Mammographic Images},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {1},
  number    = {5},
  year      = {2010},
  publisher = {The Science and Information Organization},
  author    = {H B Kekre and Saylee Gharge},
  doi       = {10.14569/IJACSA.2010.010517},
  url       = {https://doi.org/10.14569/IJACSA.2010.010517}
}