Research on Preprocessing Method for Microscopic Image of Sputum Smear and Intelligent Counting for Tubercule Bacillus

2018 2nd annual International Conference on Cloud Technology and Communication Engineering

计算机科学;无线电电子学

Li, Zhisong^1 ; Ling, Jiayao^2 ; Wu, Jing^2 ; Luo, Nian^2 ; Tan, Min^2 ; Zhong, Ping^2

School of Information Science and Technology, Donghua University, Shanghai

201620, China^1

Department of Applied Physics, Donghua University, Shanghai

201620, China^2

关键词: Automatic identification;    Background filters;    Important features;    Intelligent recognition;    Multi-frame image information;    Neural network classifier;    Pre-processing method;    Single layer perceptron;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/466/1/012112/pdf
DOI  :  10.1088/1757-899X/466/1/012112

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

In order to automatically detect bacilli in sputum smear with microscopy, an intelligent recognition method based on machine vision is presented. Firstly, a novel method with the fusion of multi-frame image information is presented to improve the quality of microscopic image of sputum smear by extending the dynamic range, and then the background filter was designed based on the single layer perceptron to recognise bacilli 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, two important features are presented to solve the difficult problem of identification and counting for the overlapping and winding bacilli. Finally, based on the above research content an EBP neural network classifier is designed for the accurate identification and counting of the bacilli. Experimental results show that the method presented in this paper is a feasible and accurate solution for bacilli automatic identification.