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Key of packaged granary grain quantity recognition —Grain bags image processing

机译:包装粮粒数量识别关键—粮袋图像处理

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A study of core problem in the packaged granary grain intelligent detection based on image recognition was conducted, and an intelligent detection method combining Fisher criterion with Adaptive Genetic Algorithm was used to solve it. We took the actual scene video as the analysis object, and the constructed Fisher criterion as the fitness function of Genetic Algorithm, while we presented a local optimization operator that enhance the diversity of the population and solve the disadvantages of poor astringency and premature occurrence. Finally, we introduced the morphology processing method to achieve excellent detection effect. Experimental results showed that this detection algorithm effectively improves the anti-jamming capability and robustness. This work provides an intelligent detection method for grain reserving management.
机译:对基于图像识别的包装粮谷智能检测中的核心问题进行了研究,并采用Fisher准则与自适应遗传算法相结合的智能检测方法进行了求解。我们以实际场景视频为分析对象,以构造的Fisher准则为遗传算法的适应度函数,同时提出了一种局部优化算子,该算子可以增强种群的多样性并解决收敛性差和过早发生的弊端。最后,我们介绍了形态学处理方法,以实现出色的检测效果。实验结果表明,该检测算法有效提高了抗干扰能力和鲁棒性。这项工作为储粮管理提供了一种智能的检测方法。

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