To achieve automatic inspection and reading capabilities of pointer-type meters in robot as the traditional method extracting the position of start and end lines on the pointer meter is not sufficiently accurate, this study proposes a new type of meter reading algorithm, solving the problem for the need of the start and end lines to be preset in advance. The traditional Hough line recognition algorithm deviates from the center line of the pointer, thereby improving the accuracy of system reading. As the reliability of the reading result cannot be assessed using the existing method, this study establishes an instrument for a reliable reading estimation model based on consistent significance. A clustering algorithm is used to achieve a consistent and significant correlation constraint detection of instrument features, which can estimate the reliability of meter readings. The experimental results show that the accuracy of the proposed instrument reading algorithm is high and that the estimated model created is stable and reliable.