说明：  在传统图像识别中的模板匹配技术面临着计算量大，存储量大的缺点，因此提出了基于遗传算法的图像识别的方法。本文提出了传统的基于遗传算法和normxcorr2结合的方法，对图像进行离散化，然后把图像识别问题变成一系列的离散点组合优化问题，再利用遗传算法对种群优化的性能，对各个控制点组合优化，让控制点与模板进行匹配，寻出最优解。最后通过实验验证遗传算法在图像识别的优点。
(In the traditional image recognition in the face template matching calculation capacity, storage capacity shortcomings, the proposed genetic algorithm based on image recognition method. In this paper, based on genetic algorithms and the traditional method of combining normxcorr2, the image discretization, then the image recognition problem into a series of discrete points of combinatorial optimization problems, and then use genetic algorithm to optimize the performance of the population, a combination of all control points optimized, so that the control points and template matching to find the optimal solution. Finally, experimental verification of the genetic algorithm through the image recognition advantages.)