A Robust Multi-Orientation Gabor Based System for Discriminating Touching White and Red Cells in Microscopic Blood Image

In many image analysis systems, segmentation is the first step. So its accuracy impacts on whole system efficiency. In normal human blood microscopic image, which contains white and red blood cells, because of high accumulation of red cells, there exist touch and overlap between these cells. They are two difficult issues in image segmentation which common segmentation algorithms cannot overcome them. Red cell has fine texture while white cell has coarse one, so texture is a very good discriminating feature for segmentation of blood cells. Gabor filters are one of the most powerful methods for texture segmentation. Blood image don´t have regular textures. Common Gabor filter banks are suitable for regular texture segmentation. So we have employed a Gabor filter bank including many orientations and few frequencies in combination with sigmoid function for blood image segmentation. Results show that our approach is efficient