Distribution Safety Monitoring Data Cleaning Technology Based on OpenPose-GLCM-Hash
With the increasing scale and complexity of modern power distribution networks,security monitoring is faced with severe challenges.Continuous security surveillance video generates massive image data.Due to the high similarity of adjacent images,data management will be inefficient and redundant if it is not effectively screened and cleaned.In this paper,an OpenPose-GLCM-Hash data cleaning technique is proposed,which combines the global texture features of Grey Level Co-occurrence Matrix(GLCM)with the human pose features extracted by improved OpenPose algorithm.Image hash code is generated by weighted combination to achieve efficient image weight removal.The experimental results show that the algorithm has high weight removal rate and low error rate in different environments,especially in noisy environments.This study provides an effective solution for the data management of power distribution safety supervision.
distribution security monitoringdata cleaningattitude estimationgray co-occurrence matrix
万方数据
维普
