曲阜师范大学学报（自然科学版）2026，Vol.52Issue(2)：79-84,6.DOI:10.3969/j.issn.1001-5337.202404.028
LVQ神经网络在图像边缘检测中的应用
Application of LVQ neural network in image edge detection
摘要
Abstract
Addressing the issues of noise sensitivity and edge blurriness present in traditional edge de-tection methods,an enhanced approach called LVQCA is proposed,which integrates the Canny operator with a learning vector quantization(LVQ)neural network.By using the Canny operator as a guidance signal for the LVQ neural network,the training process effectively captures edge information within images while enhancing the completeness and connectivity of the detected edges.Experimental results demonstrate that,compared to traditional operators like Roberts and Log,the LVQCA neural network exhibits higher accura-cy and robustness in edge detection of traffic images under adverse weather conditions,providing more pre-cise critical road information for autonomous driving.关键词
LVQ神经网络/边缘检测/Canny算子Key words
LVQ neural network/edge detection/Canny operator分类
信息技术与安全科学引用本文复制引用
张静,张晓玲,钱鹏,韩成艳..LVQ神经网络在图像边缘检测中的应用[J].曲阜师范大学学报（自然科学版）,2026,52(2):79-84,6.基金项目
安徽省教育厅自然科学基金重点项目(2022AH051980) （2022AH051980）
安徽三联学院服务机器人协同创新中心重点研究项目(zjqr24002) （zjqr24002）
安徽三联学院教育教学改革重点研究项目(23zlgc091). （23zlgc091）
