Image Recognition and Counting for the Bacilli Cell Based on the Microscopic Image

In order to automatically detect bacilli in sputum image with microscopy, an intelligent recognition method based on machine vision is presented. Firstly, a novel background filter was designed based on the single layer perceptron to realize object segmentation from background. After eliminating the short twig and small area noise, the suspicious goals and the image noise are separated. In the feature extraction, besides the base features of single bacillus two important features are presented to solve the difficult problem of identification and counting for the overlapping and winding bacilli cells. Finally, an EBP neural network classifier is designed for the accurate identification and counting of the bacilli cells. Experimental results verified the effectiveness of the presented method.