Machine Vision Based Automatic Detection Method of Indicating Values of a Pointer Gauge

Abstract

This study proposes an automatic reading approach for a pointer gauge based on computer vision. Moreover, the study aims to highlight the defects of the current automatic-recognition method of the pointer gauge and introduces a method that uses a coarse-to-fine scheme and has superior performance in the accuracy and stability of its reading identification. First, it uses the region growing method to locate the dial region and its center. Second, it uses an improved central projection method to determine the circular scale region under the polar coordinate system and detect the scale marks. Then, the border detection is implemented in the dial image, and the Hough transform method is used to obtain the pointer direction by means of pointer contour fitting. Finally, the reading of the gauge is obtained by comparing the location of the pointer with the scale marks. The experimental results demonstrate the effectiveness of the proposed approach. This approach is applicable for reading gauges whose scale marks are either evenly or unevenly distributed.

Intelligent Machine Vision Based Modeling and Positioning System in Sand Casting Process

“…(iv) Draw circles in the accumulator array shown in Figure 3 for all the values of radius defined earlier in the accumulator array, centered at the index of the edge detected; this is also called voting (drawing a circle means to add 1 to the corresponding array elements). The modern research on machine vision for tolerance detection [13] suggests novel methods to detect the dimensions with accuracy and we tried to implement our algorithm on similar lines. This system (as shown in Figures 4(a) and 4(b)) is designed such that the pouring cup of any radius should be accommodated.…”

A High-Robust Automatic Reading Algorithm of Pointer Meters Based on Text Detection

“…Then, they used RANSAC line drawing method and least square method to recognize the pointer and zero graduation line, respectively, and finally used angle method for reading. Chi et al [ 16 ] put forward an automatic reading method of pointer meter based on computer vision. They first used the method of region growing to locate the dial region and its center.…”

“…The methods proposed by Alegria [ 11 ], Belan [ 12 ] and Gao [ 14 ] can achieve a higher accuracy in the verification system with manual control of brightness and shooting angle, but have a poor robustness in industrial fields with more complex shooting environment, such as external substations. In addition, although the methods proposed by Zheng [ 13 ], Ma [ 15 ], Chi [ 16 ] and Sheng [ 17 ] have improved the robustness of automatic reading algorithms to a certain extent, these methods are weak in adapting to different meter types, and the proposed algorithms can only be applied to the meter dials with certain characteristics. For example, the extracted vertexes of quadrilateral meter dial were used to make meter rectification in Zheng’s method [ 13 ], which is not applicable to those round meters; the method proposed by Ma [ 15 ] located the meter center according to the circularity of center of rotation, which is only suitable for those meters with a circular center; the method presented in Chi’s article [ 16 ] is also only applicable to meters whose scale line is distributed within the gray scale region.…”

“…In addition, although the methods proposed by Zheng [ 13 ], Ma [ 15 ], Chi [ 16 ] and Sheng [ 17 ] have improved the robustness of automatic reading algorithms to a certain extent, these methods are weak in adapting to different meter types, and the proposed algorithms can only be applied to the meter dials with certain characteristics. For example, the extracted vertexes of quadrilateral meter dial were used to make meter rectification in Zheng’s method [ 13 ], which is not applicable to those round meters; the method proposed by Ma [ 15 ] located the meter center according to the circularity of center of rotation, which is only suitable for those meters with a circular center; the method presented in Chi’s article [ 16 ] is also only applicable to meters whose scale line is distributed within the gray scale region. The method proposed by Sheng [ 17 ] used scale line to fit the meter center, so the scale image has few characteristics, which is prone to false detection and influence by the image quality.…”

Automated Tilt Conveyor for Cylinder Head

“…Chi et al (2015) suggested the modern output of canny edge detector. The investigation of vision based machine for the detection of tolerance as well as methods in novel for identifying dimensional correction and applying algorithms [8]. Kosler (2016) introduced the process for improving safety of working environment as well as ergonomics [2,9].…”