摘要
针对桌面灰尘检测在光照变化时有灰尘与无灰尘图像相似度区分界限不明显的问题,提出一种基于兰氏距离改进的图像相似度算法。该算法融合指数函数性质,将模板图与有灰尘和无灰尘图像之间的兰氏距离转换为(0,1]区间的相似度值,同时扩大相似度差值。为增强灰尘纹理特征信息,将灰度图进行拉普拉斯算子卷积,再用共生矩阵特征提取算法提取特征参数并将其组合成一维向量。用改进后的相似度算法计算模板图与待检测图的特征参数向量相似度,根据向量相似度判断桌面是否具有灰尘。实验结果表明在300~900lux光照范围内,无灰尘图像之间的相似度高于90.01%,有灰尘与无灰尘图像之间的相似度低于62.57%。两种相似度的均值能够作为阈值,在光照变化时有效地判断桌面是否具有灰尘。
An image similarity algorithm based on Lance Williams distance was proposed to solve the problem that the boundary of similarity between dust image and dust-free image is not obvious when illumination changes in desktop dust detection.The Lance Williams distance between template image and the images with or without dust was converted to the similarity value of (0,1] and the difference of similarity values was expanded with exponential function properties in the algorithm.In order to enhance the dust texture feature information,the gray image was convolved with the Laplacian and then the feature parameters were obtained using co-occurrence matrix feature extraction algorithm and combined into a one-dimensional vector.The similarity of feature parameter vectors between template image and to-be-detected image was calculated by the improved similarity algorithm to determine whether the desktop has dust or not.Experimental results show that the similarity is more than 90.01% between dust-free images and less than 62.57% between dust and dust-free images in the range of 300~900 lux illumination.The average of the two similarities can be regarded as the threshold to determine whether the desktop has dust or not when illumination changes.
作者
张宇波
张亚东
张彬
ZHANG Yubo;ZHANG Yadong;ZHANG Bin(School of Electrical Engineering,Zhengzhou University,Zhengzhou Henan 450001,China)
出处
《计算机应用》
CSCD
北大核心
2019年第8期2414-2419,共6页
journal of Computer Applications
基金
河南省高校科技创新团队支持计划项目(17IRTSTHN013)~~
关键词
桌面灰尘检测
图像相似度
灰度共生矩阵
特征提取
光照度
兰氏距离
desktop dust detection
image similarity
gray level co-occurrence matrix
feature extraction
illumination
Lance Williams distance
作者简介
张宇波(1965—),女,山东昌乐人,副教授,博士,主要研究方向:信号处理、智能控制;通信作者:张亚东(1993-),男,河南新乡人,硕士研究生,主要研究方向:机器视觉处理,电子邮箱15137164207@163.com;张彬(1993-),男,河南荥阳人,硕士研究生,主要研究方向:机器学习、目标检测。
