Recognition of Touching Erythrocytes via Contour Radial Uniformity and Sector Region Distribution Features

The presentation of touching erythrocytes affects the Red Blood Cell counting and diagnosing in automatic blood cell analysis based on digital image processing, thus a robust and efficient recognition algorithm for touching erythrocytes is required. This paper analyses the typical features of touching erythrocytes and presents two new features to characterize them. The algorithm quantifies the radial uniformity of cell outer contours to describe the shape of the erythrocyte, and calculates the contour distribution within sector regions to efficiently approximate the gray scale distribution for texture representation. An ANN classifier was constructed based on the above features, and the discriminating rate for touching erythrocytes achieved 91.82%, which is promising and indicates the efficiency of the proposed features.