基于图像增强与边缘检测的弱特征目标轮廓检测算法

Target Contour Measurement Algorithm Based on Image Enhancement and Edge Detection

为了解决当前目标轮廓检测算法在边缘特征微弱、背景复杂环境下的轮廓提取精度较低的不足,设计了基于图像增强与边缘检测的目标轮廓检测算法。首先,基于拉普拉斯离散公式与二维傅里叶变换公式,构造了联合图像增强算子;然后,基于二阶导数梯度特征,设计了目标边缘检测算子,实现对目标周长、面积等参数的测量。实验数据显示:与当前目标轮廓提取算法相比,面对不利于测量工作的恶劣环境时,所提算法具有更高的提取精度与稳定性。

In order to solve the deficiency of low contour extraction accuracy in weak edge character, complex background environment, this paper designes algorithm for measuring the parameters of tool based on image enhancement and edge detection First, based on the Laplace discrete formula and two-dimensional Fourier transform formula, the coupling of the two image enhancement operator is constructed. Then, is based on the characteristics of the second derivative gradient, tool edge detection operator is designed for the cutting tool parameters such as perimeter, area measurement. Experimental data shows that compared with the current tool parameters measurement technology, in the face of unfavorable to measurement of bad environment,this algorithm has higher measurement accuracy and stability.