Texture Segmentation from Non-Textural Background Using Enhanced MTC

In image processing, segmentation of textural regions from non-textural background has not been given a significant attention, however, considered to be an important problem in texture analysis and segmentation task. In this paper, we have proposed a new method, which fits under the framework of mathematical morphology. The entire procedure is based on recently developed textural descriptor termed as Morphological Texture Contrast (MTC). In this work authors have employed the bright and dark top-hat transformations to handle the bright and dark features separately. Both bright and dark features so extracted are subjected to MTC operator for identification of the texture components which in turn are used to enhance the textured parts of the original input image. Subsequently, our method is employed to segment the bright and dark textured regions separately from the two enhanced versions of the input image. Finally, the partial segmentation results so obtained are combined to constitute the final segmentation result. The method has been formulated, implemented and tested on benchmark textured images. The experimental results along with the performance measures have established the efficacy of the proposed method.