Blurred video detection algorithm based on support vector machine of schistosoma japonicum miracidium

With the development of computer technology, medical microscopic image processing and recognition is one of the most important motivations to promote biomedical engineering, which not only provides a reliable and efficient method for clinical diagnosis, but also develops the medical scientific research and teaching. Because the microscopic image of the schistosome egg has impurities and complex background, it is hard to process and identify. Based on the existing researches on microscopic image identification for parasites and cells, the paper studies the egg image segmentation, feature extraction, selection, classification and recognition method with image processing and pattern recognition technology. The schistosomiasis miracidium video detection algorithm based on the Support Vector Machine (SVM) obtained through microscope the miracidium of real-time video processing, to identify and mark the miracidium in the video. This method owned higher recognition accuracy and efficiency compared with the traditional artificial recognition methods and greatly reduced the investment of human resources.