摘要
为了解决当前火焰图像边缘检测技术易受到近似亮度的影响,使其得到的边缘不够清晰、完整性不强等不足,定义了一种基于局部二值模式(LBP)耦合双阈值(LM)优化的图像边缘检测算法。将彩色图像转换为灰度图像,并根据统计分布调整图像的灰度。采用高斯滤波器平滑图像,消除噪声影响。然后,利用LBP处理图像,并采用全局阈值技术进行计算,获取边缘局部特征。通过非极大值抑制算子来得到更精确的边缘,在非极大值抑制中选择2个阈值来创建2个不同的边缘图像。为了加快这2个非极大值抑制阈值的优化过程,采用LM优化算子,优化了基于均方误差的成本函数,消除了虚假边缘的同时保留了细小边缘。此外,利用火焰图像的面积、平均值、标准差、方差等各种参数对火焰图像进行分析,从而准确得到火焰温度以及预测燃烧的稳定性。通过实验表明,与当前火焰图像边缘检测技术相比,算法能够具有更高的边缘检测质量,火焰边缘完整度更好,可以有效去除噪声和不相关的伪影。
In order to solve the defects as the low edge sharpness and edge integrity induced by susceptible to the influence of approximate brightness in the current flame image edge extraction algorithm,an image edge extraction scheme based on local binary mode coupled with double threshold levenberg-marquardt( LM) optimization was defined. The color image was transformed into gray image,and the gray level of the image was adjusted according to the statistical distribution of the image. The image was smoothed by using the Gaussian filter to eliminate the influence of noise. Then,local binary patterns( LBP) were used to process images,and global threshold technique was used to calculate the local features of edges. Then,the non-maximum suppression operator was used to get more accurate edges,and two thresholds are selected to create two different edge images in non-maximum suppression. In order to speed up the determination of non-maximum suppression thresholds,LM optimization algorithm was used to optimize the cost function based on mean square error,eliminating false edges while retaining small edges. In addition,the area,average value,standard deviation and variance of the flame image were used to analyze the flame image,thus the flame temperature can be accurately obtained,and the stability of flame combustion can be predicted. Experiments show that compared with the current flame image edge detection technology,this proposed algorithm has higher edge detection quality and better flame edge integrity,which can remove noise and irrelevant artifacts.
作者
李莉
王绪国
Li Li;Wang Xuguo(Wuhan railway vocational college of technology, Wuhan 430205, China;School of Information Engineering, Wuhan University of Technology, Wuhan 430000, China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2019年第6期9-17,共9页
Journal of Electronic Measurement and Instrumentation
基金
国家自然科学基金(60496315)
湖北省自然科学基金(2018CFB586)资助项目
关键词
边缘提取
局部二值模式
双阈值
LM优化
非极大值抑制
火焰分析
edge extraction
local binary mode
double threshold
LM optimization
non-maximum suppression
flame analysis
