A genetic algorithm（GA） optimization support vector machine（SVM） method is proposed for printing registration state recognition.Texture analysis on collected printing marks images is carried out and the moment of inertia

energy

correlation

and entropy of gray level co-occurrence matrix are extracted. The mean and variance values of gray level co-occurrence matrix are calculated and the parameters are calculated to generate 8-dimensional texture feature data. SVM model using radial basis Kernel function is established. GA is used to optimize and select the penalty factor and kernel function parameters of SVM

thus complete the recognition.Results show that the GA-SVM model can effectively recognize the printing registration and meet the real-time requirements.