A robust and high-precision automatic reading algorithm of pointer meters based on machine vision

Automatic reading of pointer meters is of great significance to meter verification and industrial inspection robots. Many automatic reading algorithms of pointer meters based on machine vision have been proposed. However, the pointer shadow problem has not been effectively solved, which hinders the automatic reading of inspection robots in complex lighting environments. Also, pointer line recognition is easily influenced by the images around the pointer. With the aim of addressing these problems, this paper proposes a robust and high-precision pointer meter automatic reading algorithm. In meter center recognition using a round-degree method, this paper uses the eight chain code shape to represent the pixel image shape to prevent abnormal calculation of the round-degree. A novel binarization threshold determination method based on the symmetry degree is proposed to segment the pointer region, which effectively solves the pointer shadow problem. In addition, for pointer recognition, this paper proposes an improved random sample consensus (RANSAC) algorithm to overcome background image interference. The experimental results prove that the algorithm effectively removes pointer shadows and that the reading precision is high.