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In order to adapt to the requests of onsite rapid detection technique of Escherichia coli (E.coli) for the safety of agricultural products, a rapid E.coli recognition method based on shape and color feature parameters was proposed. Principal component neural network was used to improve the recognition ability. Principal component analysis was applied to the 14 extracted feature parameters, including Hu’s moment invariants, shape factor, denseness and saturation, et al. A three-layer BP neural network model based on the principal components was constructed. Compared with traditional BP neural network, the configuration of the principal component neural network was simpler, the training time was shorter and the recognition accuracy was higher. The recognition accuracy of the principal component neural network can arrived at 91.33%. 