针对现有包装设备上对摄像机标定中传统优化算法存在的缺点，如对初始值敏感、收敛性差、易陷入局部最优解等，研究了量子粒子群优化算法在摄像机标定中的应用，提出了一种基于智能优化的摄像机标定方法，并给出了具体的步骤。实验结果表明该标定方法可以克服传统算法的不足，具有较高的精度，可以满足计算机视觉在包装工程中的应用。

The application of an improved quantum particle swarm optimization algorithm（QPSO）in camera calibration was studied to overcome the drawbacks of traditional optimization algorithms in camera calibration, such as sensitive to original value, poor astringency, and easy to relapse into local optimization. A camera calibration method based on intelligent optimization algorithm was put forward and the calculation procedures were given. Calibration experiments results showed that the method can overcome the drawbacks of traditional optimization algorithms, has higher precision, and meet the application requirements of computer vision in packaging engineering.