Abstract
The application of remote digital video surveillance and image recognition technology in online monitoring of power equipment is conducive to timely equipment maintenance and troubleshooting. In order to solve the problem of slow speed and large amount of computation of traditional template matching algorithm for power image recognition, a second template matching algorithm for fast recognition of target image is proposed in this article. Firstly, a quarter of the template data is taken and matched within a quarter of the source image, and a reasonable error threshold is given in the matching process. Then, the neighborhood of the minimum error point in rough matching is matched to get the final result. Finally, the algorithm is applied to identify the power equipment and detect the abnormal state of the power equipment. The experimental results show that the matching algorithm can not only accurately locate and identify power equipment and detect equipment faults, but also greatly improve the matching speed compared with other commonly used template matching algorithms.
Highlights
The rapid growth of the national economy is the rapid growth of industrial and agricultural electricity demand, the shortage of power supply, and the frequent occurrence of power shortage, which has brought unprecedented challenges to the power system
Because the monitoring image is too large, and when the surface of power equipment is defective, it is difficult for the human eye to distinguish the subtle changes of the image
Because the background of power equipment image in the substation is complex and the illumination often changes, we can find out the part of the equipment which has some special characteristics as the template feature, and find the location of the equipment in the image according to the template feature in the image to be recognized
Summary
The rapid growth of the national economy is the rapid growth of industrial and agricultural electricity demand, the shortage of power supply, and the frequent occurrence of power shortage, which has brought unprecedented challenges to the power system. Luo et al.[17] discussed the application of image processing in recognition technology in the remote video monitoring system. The shape representation method based on geometric moment invariants and similarity measures achieve good results in the process of identifying substation power equipment. Image recognition[7] refers to the technology of using computers to process, analyze, and understand images in order to identify targets and objects of different modes. In order to test the performance of the secondary template matching algorithm proposed in this article, the absolute error method, the correlation coefficient R method, and the secondary matching method proposed in this article are respectively used for template matching on the two images, and the results are compared.
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