摘要
针对纸张图像在复杂纹理背景下识别难度大、特征稳定性差的问题,提出一种基于ORB(Oriented FAST and Rotated BRIEF)算法的数字化纸张信息识别方法。该方法利用高效的关键点提取与描述技术,提升了纸张表面批次标识、水印结构、印刷编码等视觉信息的识别精度与实时性。在典型纸张图像样本上进行实验,结果显示,该方法具有识别速度快、抗干扰能力强、匹配准确率高等优势。研究结果对推动纸品追溯管理和智能检测系统建设具有重要的工程价值与实际意义。
Aiming at the problems of high recognition difficulty and poor feature stability of paper images in complex texture backgrounds,this paper proposes a digital paper information recognition method based on ORB(Oriented FAST and Rotated BRIEF)algorithm.This method utilizes efficient key point extraction and description technology to enhance the recognition accuracy and realtime performance of visual information such as batch identification,watermark structure,and printing code on the paper surface.Experiments were conducted on typical paper image samples.The results show that this method has the advantages of fast recognition speed,strong anti-interference ability and high matching accuracy.The research results have significant engineering value and practical significance for promoting the construction of paper product traceability management and intelligent detection systems.
作者
刘娜
王姝
LIU Na;WANG Shu(Xi’an Aeronautical Polytechnic Institute,Xi’an 710089,China)
出处
《造纸科学与技术》
2025年第8期114-117,共4页
Paper Science And Technology
基金
2023年度西安航空职业技术学院科研计划研究项目(23XHZK-10)。
关键词
ORB算法
图像识别
纸张信息
特征提取
数字化感知
ORB algorithm
image recognition
paper information
feature extraction
digital perception
