基于数学形态学的设备图像边缘检测方法研究

Research on Edge Detection of Device Image Based on mathematical morphology

为进一步提升图像边缘检测方法的检测性能,基于数学形态学提出一种设备图像的边缘检测方法。其中,选择抗噪形态学边缘检测算法作为基础的算法,并从算法的结构元素以及滤波方法两个方面对算法进行优化,以提升算法的抗噪能力与边缘检测水平。实验结果表明,与其他检测算法相比,本研究提出的改进抗噪数学形态学图像边缘检测算法具有更加优秀的抗噪能力与边缘检测水平,在无噪声环境下的信噪比和均方差分别为24.015和260.128;与其他边缘检测算法相比,本研究提出的算法在各种噪声环境下始终保持最佳的检测水平和抗噪能力。以上结果表明,本研究提出的改进抗噪数学形态学图像边缘检测算法能够取得良好的边缘检测效果,同时还具备较强的抗干扰能力,十分适用于设备的监测,具有一定的实际应用价值。

In order to further improve the detection performance of current image edge detection methods,an edge detection method of device image based on mathematical morphology is proposed.Among them,the anti noise morphological edge detection algorithm is selected as the basic algorithm,and the algorithm is optimized from two aspects:the structural elements of the algorithm and the filtering method,in order to improve the algorithm's anti noise ability and edge detection level.The experimental results show that,compared with other detection algorithms,the improved anti noise mathematical morphology image edge detection algorithm proposed in this study has more excellent anti noise ability and edge detection level,and the signal-to-noise ratio and mean square deviation of this algorithm are 24.015 and 260.128 respectively in the noiseless environment;Compared with other edge detection algorithms,the algorithm proposed in this study consistently maintains the optimal detection level and noise resistance in various noisy environments.The above results show that the improved anti noise mathematical morphology image edge detection algorithm proposed in this study can achieve good edge detection effect,and also has strong anti-interference ability,which is very suitable for equipment monitoring and has certain practical application value.