Common Posterior Animal Image Recognition System in Activated Sludge
With the improvement of people's living standards and the improvement of urbanization level, urban sewage discharges have increased rapidly. Therefore, urban sewage treatment has become more and more important. At present, municipal sewage treatment mainly uses activated sludge method that is, using microbial metabolism in activated sludge to purify water quality. These microorganisms can not only purify water, but also predict the water quality caused by the influence of water quality environment. Monitoring, analyzing and judging various changes in microorganisms can adjust the process control of the sewage treatment system adjusted scientifically and in a timely manner. Among these microorganisms, protozoa and metazoans have very important indications. Therefore, it is important to identify, classify and count protozoa that are common in activated sludge. In this paper, the microscopic image recognition of protozoa and metazoan in the activated sludge system of Yunnan Province was studied. Based on the characteristics of microscopic images, the image recognition of the original metazoan was studied and the protozoa and metazoans in the activated sludge system were introduced. The counting algorithm and implementation scheme lay the foundation for further research on the counting algorithm. Experiments show that the recognition accuracy is proportional to the resolution of the image. When the resolution is high, the corresponding image recognition rate is higher. Through experiments, it is also verified that it can accurately identify the number of different insects.