Natural image segmentation using morphological mathematics and fuzzy logic

The segmentation of natural images remains a challenging task in image processing. Many methods have been proposed in the literature regarding algorithms for the segmentation of such images. Many of the algorithms are complex in nature and inefficient in practice with unaltered images. In order to efficiently use the algorithms it is beneficial to preprocess the natural images. However, natural images often involve subjects and background that are not easily quantified with crisp preprocessing parameters. To this, we will show the use of grey-scale morphological operators coupled with fuzzy image enhancement with natural images is an efficient and noncomplex method that more accurately isolates the region of interest in the image and will define a novel combination of grey-scale morphological operators for use with natural images.