基于改进Canny算子的电力设备图像检测研究

图像边缘检测技术在电力行业的应用越来越广泛,但仍然存在些许问题限制了其在工程中的实际应用。对于复杂的现场电力设备图像,结合最优阈值灰度分割法和Canny算子等图像处理技术,提出了基于改进Canny算子检测电力设备图像。首先利用最优阈值灰度分割法得到的阈值作为Canny算子的高阈值Th;然后利用高低阈值的对应关系确定低阈值Tl,。由此可实现改进Canny自适应检测电力设备图像的目的。实验结果表明,该方法可取得较为理想的边缘检测效果,具有一定的实用性。

The electricity equipment image detection research based on improved Canny operator

Edge detection technology applies in the electric power industry more widely, But there are still a little problems limiting its practical application in engineering. For complex on-site power equipment image, using the optimal threshold gray segmentation and Canny edge detection technology, put forward detecting the electricity equipment image based on improved Canny operator. First, use the optimal threshold gray segmentation to determine the Canny high threshold Th, which play a decisive role in edge detection; and use the corresponding relation to determine low threshold Tl, which Play a supplemental role in edge detection, thereby can realize that the improved Canny operator adaptively detects the electricity equipment image. The experimental results show that, this method can achieve the desired edge detection, and has a certain practical.