Published on February 2016 | Image processing, Softcomputing

Retinal Vessel Segmentation using Infinite Perimeter Active Contour with Hybrid Information Model

The aim of the segmentation in image processing is to represent images in an easy and meaningful manner by dividing them into a different group. It mainly helps for medical imaging and surveillance. We propose an infinite active contour model that uses hybrid region information of the image which allows for better detection of small branching like structures than the other models. Furthermore, for better general segmentation performance, the proposed model takes the benefit of using different types of region information, such as the combination of intensity information and local phase based enhancement method. The local phase based enhancement method is used for its superiority in conserving vessel edges while the given image intensity information will ensure a correct feature’s segmentation. We estimate the performance of the proposed model by applying it to two public retinal vessel image datasets. And also it compares the performance of unsupervised segmentation using three influential filters