Design Of Real-time Intelligent Recognition System Based On Plankton Target Image Processing

The number and distribution of marine plankton in ocean water bodies have very important significance in the research of the biogenic elements in the biogeochemical cycles (such as C cycle, N cycles) and research of global climate. How to achieve a large area automated insitu detection of abundance and biomass distribution of dominant species, is an very important issue to be solved in the exploration of sea.In order to meet the demands of real-time statistics for classification,this paper proposes a design for real-time intelligent recognition system for marine plankton target with high recognition rate. This paper acquires real-time image with CCD sensor, develops target frame selection in the processing of frames. A fast segmentation based on background subtraction instead of traditional iteration is proposed. Fast linear classifier with adaptive feature extraction is achieved for target classification.At the same time,this paper achieves parallel processing with load balancing. Results of experiments show that the system reached real-time recognition while average single-frame recognition time was less than 29.1 ms and recognition rate was as high as 91%.