Pointer type instrument reading automatic identification method based on Faster R-CNN and U-Net

Abstract

The invention relates to the field of machine vision, and discloses a pointer type instrument reading automatic identification method based on Faster R-CNN and U-Net, and the method comprises: S1), making a Faster R-CNN data set; S2) establishing a Faster R-CNN network model, and respectively training and testing the Faster R-CNN network model; S3) constructing a U-Net network model, establishinga loss function L, and respectively training and testing the U-Net network model; S4) fitting a scale line contour by utilizing a scale line segmentation result; S5) calibrating the dial image by using perspective transformation; S6) detecting a pointer area by utilizing a Faster R-CNN network model; and S7) obtaining a pointer inclination angle of the dial calibration image and a final result. According to the invention, the Faster R-CNN model is adopted to replace ORB and other traditional corner detection algorithms, so that the accuracy of detecting the area where the instrument dial and the instrument pointer are located is improved; and a Hough transform algorithm is replaced by an image segmentation and contour fitting method, a U-Net model and a corresponding loss function are redesigned for the characteristics of the electric power instrument, and the automatic identification accuracy is high.

Description

technical field [0001] The present invention relates to the field of machine vision, in particular to a pointer meter reading automatic recognition method based on Faster R-CNN and U-Net. Background technique [0002] A large number of pressure gauges, ammeters, oil temperature gauges and other meters in substations are mostly designed as pointer instruments in consideration of economic cost and electromagnetic interference in the environment. With the development of the economy, inspection robots have been introduced into more and more substations to replace manual inspections and greatly improve the automation level of substations. Inspection robots can conveniently collect a large number of meter images in substations. For these image data, especially pointer meter image data, how to realize automatic recognition of their readings is of great significance for further improving the automation level of substations. [0003] The process of automatic identification of pointe...

AI Technical Summary

Problems solved by technology

[0004] The present invention is to solve the problem that the accuracy rate of the traditional corner point detection and Hough transform method to automatically identify the image reading of the pointer meter is not high, and proposes a method for automatic recognition of the reading of the pointer meter based on Faster R-CNN and U-Net

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