基于木材微观特征的BP神经网络算法红木识别研究  

Research on Recognition of Rosewood Based on BP Neural Network Algorithm Based on Microscopic Characteristics of Wood

作　　者：朱正坤 许艳青 陈年[1] ZHU Zheng-kun;XU Yan-qing;CHEN Nian(Jiangxi Environmental Engineering Vocational College,Ganzhou 341000,Jiangxi,P.R.China)

机构地区：[1]江西环境工程职业学院,江西赣州341000

出　　处：《林产工业》2024年第1期26-30,60,共6页China Forest Products Industry

基　　金：江西省教育厅科学技术研究项目(GJJ2105402);江西省林业科技创新项目(创新专项〔2023〕35号)。

摘　　要：我国实木家具产业链发展较为成熟。作为一种珍贵木材,红木在实木家具产业中占有重要地位,我国对红木资源的进口量也在逐年增加。传统识别红木的方法主要依靠人工经验,而准确科学地识别红木种类对于红木家具产业和红木工艺品都具有重要的意义。本文提出了一种基于木材微观特征的红木识别方法,并利用BP神经网络算法,建立了识别模型,表现出较好的识别效果,可为红木树种检测提供新方法。The development of China's solid wood furniture industry is relatively mature.As a precious raw wood material,rosewood plays an important role in the solid wood furniture industry.The number of imported rosewood in China has also increased year by year.The traditional identification method of rosewood categories mainly relied on the experience of professionals,so accurate and scientific identification of rosewood was very important for both furniture industry and handicrafts.In this article,a rosewood recognition method based on the surrounding features of wood was proposed.The BP neural network algorithm was used to establish a recognition model,which has been proven to have good recognition effect and can provide a new method for the identification of rosewood.

关 键 词：红木识别 特征识别 BP神经网络 红木 微观特征 

分 类 号：TS653[轻工技术与工程] TS396