A generation method of insulator region proposals based on edge boxes

High-quality insulator region proposals play important roles in the process of transmission line inspection images. A generation method of insulator region proposals based on edge boxes is proposed in this paper, and edge boxes are applied to the localization of insulators in inspection images creatively. We take a series of operations to generate insulator region proposals: K-means cluster is used on curvature scale space(CSS) points extracted from edge images, the most appropriate cluster number is chosen, and the circle is drawn on the insulator subclass. We consider the characteristics of insulators' edge images, and combine these characteristics with edge boxes. As a result, more insulator region proposals are displayed. The experimental results show that our method can effectively reduce the interference area, meanwhile, has high quality of region proposals with fast calculation speed.

Self-adaptive scale pedestrian detection algorithm based on deep residual network

Purpose–The conventional pedestrian detection algorithms lack in scale sensitivity.The purpose of this paper is to propose a novel algorithm of self-adaptive scale pedestrian detection,based on deep residual network(DRN),to address such lacks.Design/methodology/approach–First,the“Edge boxes”algorithm is introduced to extract region of interestsfrompedestrian images.Then,the extracted boundingboxesare incorporatedto differentDRNs,one is a large-scale DRN and the other one is the small-scale DRN.The height of the bounding boxes is used to classify the results of pedestrians and to regress the bounding boxes to the entity of the pedestrian.At last,a weighted self-adaptive scale function,which combines the large-scale results and small-scale results,is designed for the final pedestrian detection.Findings–Tovalidatetheeffectivenessandfeasibilityoftheproposedalgorithm,somecomparisonexperiments have been done on the common pedestrian detection data sets:Caltech,INRIA,ETH and KITTI.Experimental resultsshowthattheproposedalgorithmisadaptedforthevariousscalesofthepedestrians.Fortheharddetected small-scale pedestrians,the proposed algorithm has improved the accuracy and robustness of detections.Originality/value–By applying different models to deal with different scales of pedestrians,the proposed algorithm with the weighted calculation function has improved the accuracy and robustness for different scales of pedestrians.