Edge Detection of High-Voltage Porcelain Insulators in Infrared Image Using Dual Parity Morphological Gradients

Abstract

A new edge detection operator based on dual parity morphological gradients is proposed, in order to accurately segment a porcelain insulator string in an infrared image before the identification and diagnosis of deteriorated insulators by the extracted thermal information. When applied to the double-shed insulators, the proposed detector is capable of effectively eliminating the blurred region between the upper and lower sheds as well as preventing over-segmentation by combining both odd and even structural elements. Compared with the multiscale morphological gradient algorithm, this technique reduces the size of the maximum structural elements to optimize the computational complexity. A quantitative evaluation using PSNR, IoU, and FPR indexes shows that the new technique outperforms other common edge detectors. In addition, the experiments on thousands of real infrared images demonstrate the detector to be highly effective despite its low complexity.