A Planar-Dimensions Machine Vision Measurement Method Based on Lens Distortion Correction

Lens distortion practically presents in a real optical imaging system causing nonuniform geometric distortion in the images and gives rise to additional errors in the vision measurement. In this paper, a planar-dimensions vision measurement method is proposed by improving camera calibration, in which the lens distortion is corrected on the pixel plane of image. The method can be divided into three steps: firstly, the feature points, only in the small central region of the image, are used to get a more accurate perspective projection model; secondly, rather than defining a uniform model, the smoothing spline function is used to describe the lens distortion in the measurement region of image, and two correction functions can be obtained by fitting two deviation surfaces; finally, a measurement method for planar dimensions is proposed, in which accurate magnification factor of imaging system can be obtained by using the correction functions. The effectiveness of the method is demonstrated by applying the proposed method to the test of measuring shaft diameter. Experimental data prove that the accurate planar-dimensions measurements can be performed using the proposed method even if images are deformed by lens distortion

Parameters of Zhang’s method.

<p>Parameters of Zhang’s method.</p

Calibration patterns for camera.

<p>Calibration patterns for camera.</p

Fitting the structured light plane.

<p>Fitting the structured light plane.</p

The measurement results of the proposed method (mm).

<p>The measurement results of the proposed method (mm).</p

The imaging of gauge block.

<p>The imaging of gauge block.</p

The measurement results of 8 mm Gauge block.

<p>The measurement results of 8 mm Gauge block.</p

The calibration model of the paper.

<p>The calibration model of the paper.</p

Overview of the structured light vision system.

<p>Overview of the structured light vision system.</p

Zhang’s calibration model.

<p>Zhang’s calibration model.</p