Plankton classification counterBy using a high-resolution camera to capture images of plankton in water samples, the collected images are preprocessed, including denoising, contrast enhancement, and other operations. Then, the shape, size, color, and other feature information of plankton in the images are extracted. Finally, through a pre established plankton database and machine learning algorithms, the extracted features are compared and matched to achieve automatic identification and counting of plankton.

　　Plankton classification counterFunction:

1. Automatic classification and counting: The instrument captures real-time images of the sample through optical or electromagnetic sensors, and compares the collected images with plankton images in the database to achieve automatic classification and counting. Some devices are also equipped with fluorescent detectors that can identify specific types of phytoplankton, further improving recognition rates and accuracy.

2. Morphological parameter analysis: The instrument can analyze and obtain morphological parameters such as area, perimeter, volume, length, width, major axis, minor axis, and equivalent diameter for each algal and planktonic organism. These parameters help researchers to gain a deeper understanding of the ecological characteristics and biomass of plankton.

3. Data statistics and report generation: The instrument can automatically calculate ecological indicators such as evenness index, individual density of algae or plankton, density of algae cells or plankton, biomass, etc. Automatically provide a classification and counting statistical report, indicating dominant species and dominance, and sorting by dominant species. The data can be exported in Excel format for further statistical analysis.