基于小生境遗传算法的激光切割快速模板匹配

为了解决激光切割视觉识别系统对大幅面多目标图像识别实时性差、对带有偏角的目标识别率低甚至出现无法识别等问题,采用小生境遗传算法,对大幅面多目标匹配识别算法进行了理论分析和实验验证。结果表明,无论目标有无旋转,该算法都能达到100%识别,算法运算时间比传统算法快5倍～10倍。该算法在识别带有旋转角度的多目标时,具有很好的实用性。

Fast template matching for laser cutting based on niche genetic algorithm

In order to solve the problem that the real-time performance of the laser cutting visual identity system was poor in the recognition of large and multi-target images, and the recognition rate of targets with deflection angle was low or even zero, niche genetic algorithm was used to study the large-surface multi-target matching recognition algorithm. Theoretical analysis and experimental verification were carried out. The results show that, whether the target is rotating or not, the algorithm can reach recognition rate of 100%. The computation time of the algorithm is 5 times~10 times faster than that of the traditional algorithm. The algorithm has good practicability in identifying multiple targets with rotation angle.