Non-destructive testing technology for intelligent identification of foreign objects in cosmetics based on BP algorithm

Jingjing Xu
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Abstract

To solve the problem that the presence of foreign matters in cosmetics will affect the safety and health of consumers and is not conducive to the development of the cosmetics industry, an intelligent identification system for foreign matters in cosmetics is established using the improved BP algorithm. Scan cosmetic samples to identify foreign matters and extract foreign matter features, so as to achieve non-destructive detection of foreign matters in cosmetics. Comparing the traditional BP algorithm, Faster R-CNN algorithm and the improved BP algorithm, the results show that the convergence time of the improved BP algorithm is 60 s and 30 s earlier than that of the traditional BP algorithm and Faster R-CNN algorithm respectively; Whether there is noise or not, the recognition rate of the improved BP algorithm is always higher than that of the traditional BP algorithm and Faster R-CNN algorithm. The accuracy rate of the improved BP algorithm is between 0.88 and 0.96, the accuracy rate of the traditional BP algorithm is between 0.57 and 0.75, and the accuracy rate of the Faster R-CNN algorithm is between 0.76 and 0.81. This shows that the improved BP algorithm can realize the nondestructive detection of foreign matters in cosmetics, ensure a high accuracy and fast speed, and provide consumers with a sense of safe use of cosmetics, it can also improve consumers’ satisfaction with the use of cosmetic products.
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基于BP算法的化妆品异物智能识别无损检测技术
针对化妆品中异物存在会影响消费者安全健康,不利于化妆品行业发展的问题,采用改进的BP算法建立了化妆品中异物智能识别系统。扫描化妆品样品识别异物,提取异物特征,实现化妆品中异物的无损检测。对比传统BP算法、Faster R-CNN算法和改进BP算法,结果表明:改进BP算法的收敛时间分别比传统BP算法和Faster R-CNN算法早60 s和30 s;无论是否存在噪声,改进BP算法的识别率始终高于传统BP算法和Faster R-CNN算法。改进后的BP算法准确率在0.88 ~ 0.96之间,传统BP算法准确率在0.57 ~ 0.75之间,Faster R-CNN算法准确率在0.76 ~ 0.81之间。这说明改进后的BP算法可以实现化妆品中异物的无损检测,保证准确性高、速度快,给消费者提供化妆品使用的安全感,也可以提高消费者对化妆品的使用满意度。
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