自适应阈值图像边缘检测方法  

Adaptive Thresholding Based Edge Detection Approach for Images

作　　者：李敏花[1] 柏猛[1] 吕英俊[1] 

机构地区：[1]山东科技大学电气信息系,济南250031

出　　处：《模式识别与人工智能》2016年第2期177-184,共8页Pattern Recognition and Artificial Intelligence

基　　金：山东省自然科学基金项目(No.ZR2014FQ020;ZR2014FM002;ZR2012FQ018);中国科学院自动化研究所复杂系统管理与控制国家重点实验室开放课题项目(No.20140109)资助~~

摘　　要：针对噪声图像的边缘检测问题,提出自适应阈值图像边缘检测方法.该方法以二维高斯函数的微分算子为基础,通过构建多方向边缘检测滤波器计算图像梯度.为减少噪声对图像梯度的影响,提出根据候选阈值自适应确定滤波器尺寸的方法.在确定滤波器尺寸的基础上,进一步提出滞后阈值的自适应选择方法.为检验文中方法的性能,在不同噪声情况下,分别对滤波器尺寸、滞后阈值与边缘检测方法性能间的关系进行实验.实验表明,文中方法可根据图像噪声情况自适应选择滤波器尺寸和滞后阈值,具有良好的抗噪性能.To detect the edge of noisy image, an adaptive thresholding based edge detection approach is proposed. In this approach, the differential operators of the two-dimensional Gaussian function are used to design the multi-oriented edge detection filter. The image gradient is computed based on the designed fihers. To reduce the effect of noise to the gradient image, an adaptive method is proposed to determine the fiher size based on the candidate thresholds. After the filter size is determined, an adaptive thresholding method is proposed to select the hysteresis threshold. The proposed edge detection approach is evaluated under different noise conditions in experiments. The relationships among filter sizes, hysteresis thresholds and the proposed algorithm performance are studied. Experimental results demonstrate that the proposed approach determines the filter size and hysteresis threshold based on the image noise adaptively and it produces good anti-noise performance.

关 键 词：边缘检测 图像梯度 滤波器尺寸 滞后阈值 自适应阈值 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]