Image recognition of personnel hazard sources in electric power aerial work scenarios considering masking effects

The conventional image recognition method in electric power altitude working scene mainly uses DPM (deformable part model) deformation component model, which is vulnerable to the changes in the micro scale of personnel, resulting in poor image recognition performance. Therefore, a method of image recognition of personnel hazard sources in the electric power aerial work scene considering the masking effect is proposed. That is to say, the identification characteristics of the hazard source image of the personnel in the electric power aerial work scene are extracted, and the image recognition algorithm of the hazard source image of the personnel in the electric power aerial work scene is designed considering the masking effect, thus completing the hazard source image recognition. The experimental results show that the designed electric power aerial image recognition method has high recall rate, accuracy rate, average intersection/merge ratio, accuracy mean and F1 value, which proves that the designed image recognition method has good recognition effect, reliability and certain application value, and has made certain contributions to improving the quality of electric power aerial work and reducing the risk of electric power operation.