Objective

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Sealing strips play an important role in the automotive industry. However

accurate results in the measurement of sealing strips are difficult to obtain due to the large deformation of their complex contour. This study proposes a novel automatic vision-based deviation measurement method for cross sections of flexible sealing strips. With this method

the matching relationship between the local contour of the captured image and the reference contour of the design drawing is computed using a two-stage image contour registration algorithm. Then

the deviation calculation is performed to evaluate the quality of sealing strips.

Method

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The method involves three steps:global registration of the contours of the captured image and reference drawing

local registration of the contours of the captured image and reference drawing

and calculation of deviations. Global registration includes three sub-steps:corner extraction

initial registration

and fine-tuning. First

corners of the contours of the sealing strips for computer vision-based measurement are extracted using a multi-resolution-based contour corner extraction algorithm. Second

on the basis of the idea of minimizing the mean square error

an exhaustive search method is applied on the corner sets of the contours of the captured image and reference drawing to obtain the matched corner pairs and affine transformation matrix. Finally

to improve the accuracy of the initial registration

the corner pairs with larger position deviation than the average position deviation are removed from the matched corner sets

and the remaining matched corners are fed into the linear regression equation to fine-tune the affine transformation matrix. On the basis of global registration

local registration aims to determine the corresponding relationships between the local contours of the captured image and reference drawing. The shape descriptors extracted from the two global contours include shape representation and restrictions of the local contours

and the similarity of shape descriptors is used to obtain the optimal result of local registration. After the global and local registrations

the positional deviations of the sealing strips are measured on the basis of the corresponding predefined instances of positional tolerances. Here

the instances of positional tolerances are defined on the reference drawing and are used in the calculation of corresponding deviations. For all deviations

if the measured value is within the corresponding tolerance

then the quality check passes. This study concentrates on the distance and angular deviations

such as point offsetting

point distance limitation

and angular positional deviations. Point offsetting deviation refers to the offsetting distance from the original point defined on the contour of the reference drawing to the corresponding point on the contour of the captured image. The corresponding point is obtained by the similarity between two shape descriptors calculated in the previous local registration. Point distance limitation deviation refers to the maximum distance from the point on the corresponding line segment of the measurement segment to the corresponding datum line on the contour of the captured image. Point distance limitation tolerance indicates the tolerable distance from the original point to the datum line defined in the reference drawing. For angular positional deviation

the intersection of the two perpendicular bisectors of the two tolerance lines defined in the standard contour is computed as the rotation center of the angular positional deviation. In the measurement

the angular positional deviation is quantified as the value of the angle between the line segments from the barycenter of the measured local contour of the captured image to the rotation center of the angular positional deviation and from the barycenter of the standard local contour of the reference drawing to the rotation center of the angular positional deviation. Finally

the product quality can be assessed automatically on the basis of the tolerances and deviations of the sealing strips.

Result

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In this study

the sealing strips are registered using a two-stage registration algorithm

and various deviations are measured between the local contours of the captured image and reference drawing. The proposed method has been tested in the actual production process. Several types of sealing strips have been tested during the experiments

whereas all captured images of the actual products have been rotated to increase the number of testing images. Finally

experimental results show that the method achieves good stability and reliability and is invariant to the rotation of the position of the sealing strips. These results are consistent with the manual testing results. Therefore

the system can effectively promote the development of automated testing for sealing strips.

Conclusion

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This study proposes a novel vision-based deviation measurement method for flexible sealing strips. The proposed method achieves good stability and reliability in the actual production process

as well as effectively performs the deviation measurement and quality inspection of flexible products. The proposed method can accelerate the development of automated quality inspection because it can automatically measure the deviation of sealing strips.