A Dualistic Sub-Image Histogram Equalization Based Enhancement and Segmentation Techniques with NN for Medical Images

-Histogram Equalization is a contrast enhancement technique in the image processing which uses the histogram of image. Segmentation of image plays a vital role in many medical imaging applications by automatically locating the regions of interest. Segmentation of image is the more crucial functions in figure analysis and processing. The segmentation results of a figure affect all the subsequent processes of image analysis. This is necessary to develop medical figure segmentation algorithms that are accurate and efficient. In this work; develop a dualistic sub-image histogram equalization based enhancement and segmentation techniques. Dualistic sub image histogram equalization (DSIHE) which divides the image histogram into two parts based on the input mean and median respectively then equalizes each sub histogram independently. Further to enhance work, use NN to present better result as compare to previous work. The proposed method has been tested and evaluated on several medical images. In paper, the medical figure is lineated and extracted out so that it can be viewed individually. Then results demonstrate that the developed algorithm is highly efficient over hierarchical grouping technique. It is valid using the performance measures such as completeness and clearness. For the implementation of this proposed work; use the GUI and NN Toolbox under Matlab software