Microorganism Image Counting Based on Multi-threshold Optimization

摘要

In view of the characteristics of multiple targets, uneven distribution of gray scale and multiple peaks in the histogram in microscopic image of sewage, a multi-threshold image counting method based on improved particle swarm optimization (PSO) was proposed in this paper to effectively solve the problems of error counting and leakage counting. We extended the two-dimensional maximum entropy algorithm to design the objective function by using of exponential entropy and adopted an improved PSO algorithm to acquire its maximum value and the best image segmentation effect. Furthermore, the breadth-first search (BFS) algorithm was applied to complete the microorganism marker and counting in the segmented images. Compared with other methods, the counting scheme in this paper achieved better anti-interference ability and higher counting precision.