Rapid detection of total number of bacteria in food using digital micro-image identification technique

A detection system for recognizing the total number of bacteria in food was developed. The system based on computer vision and artificial neural network technique can meet the need of detecting total number of bacterial in food rapidly and accurately. The software of the system was integratively programed by C++ language. By using BP neural network technique to analyze the microscopic image of food, the frame acquisitive counts are less than 500 and analysis-time of each group image (10 frames) is less than 30 s. Actual tests show that the results of milk juice and beef are of no significant differences between the new system and traditional method (p>0.05).