Application Of Edge Detection In Image Of Power Equipment

As is known to all,people need electricity in their life and work.The rapid development of economy has promoted the ever-expanding demand for electricity.When all the power equipment is intact and can operate smoothly,the efficiency of electricity production and transportation can be improved.However,to prevent the damage of power equipment,to ensure the safety of its operation,the maintenance or replacement of equipment,is also a more realistic and effective measure,indispensable.With the advent of the intelligent era,electric power enterprises have gradually introduced the new network digital system,such as remote monitoring to make the work process more convenient,and indirectly optimize the whole system of the electric power industry.Of course,digital image processing plays a very important role in it.and the extraction of edge information plays a key role in the effect of image post-processing.This paper first introduces the basic theory of power equipment image,image processing,traditional edge detection and so on,and then focuses on the analysis of mathematical morphology related concepts.The new mathematical morphology is supported by rigorous set theory.Although the algorithm is simple,the solid theoretical foundation verifies its reliability.It has been widely applied in image processing and analysis,and also extended to other fields.From this point of view,mathematical morphology can open up a new path in the future research field.If the traditional mathematical morphology only depends on the fixation of a single structural element,the image processing effect is not ideal,nor can it be applicable to all images.Based on this,this paper analyzes the characteristics of power equipment images,gives full play to the advantages of mathematical morphology in edge detection,and continues to improve and perfect.By comparing the effects of different characteristics of mathematical morphological structural elements on edges,and integrating structural elements of different scales,directions and shapes,a new type of adaptive weight operator with multi-scales and multi-structures is proposed to extract edges from images of power equipment.The algorithm also realizes the function of automatic selection of weights.A large number of experimental results show that the improved algorithm can not only ensure that the edge details can be extracted well,but also eliminate the influence of noise to a greater extent.The algorithm in this paper can provide a good reference value for the power industry in equipment monitoring,and the prospect is considerable.