Detecting and error-correcting method capable of rapidly and accurately obtaining element center and deflection angle

Abstract

A detecting and error-correcting method capable of rapidly and accurately obtaining an element center and a deflection angle is disclosed. Interested edge area can be rapidly and accurately found out through an automatic edge area extraction method based on combination of binary morphology and image reduction, and subsequent edge extraction image scope is minimized as possible. Pixel level edge is roughly positioned at first, and accordingly a sub-pixel edge is rapidly extracted by one-dimensional curve fitting method. The method overcomes the defect of complex algorithm of a conventional sub-pixel edge extraction algorithm based on two-dimensional images, and the time of extracting accurate sub-pixel edge can be shortened. Weighted least square rectangular edge fitting algorithm based on linear hazen paradigm can detect straight lines on any positions of an image, and effectively minimizes influence of outlier on fitting precision due to uneven edges. The central positions of a plurality of elements and deflect angles can be rapidly and accurately detected at once, and the efficiency of visual detection is improved.

Description

technical field [0001] The invention relates to the technical field of image processing used by the vision system of a placement machine in the surface mounting process of electronic components, and specifically relates to a detection and deviation correction method for quickly and accurately obtaining component centers and deflection angles. Background technique [0002] When the multiple suction nozzles of the placement machine pick up the patch components, due to component transportation, feeding, mechanical positioning of the suction nozzles, pneumatic suction and other actions, two problems may be caused: one is the center of the sucked component and the center of the suction nozzle. The center does not coincide; the second is that there is an angular deviation between the pick-up position of the component and the target placement position. These problems will have a serious impact on the accurate placement of components, so position deviation compensation and angle cor...

AI Technical Summary

Problems solved by technology

[0002] When the multiple suction nozzles of the placement machine pick up the patch components, due to component transportation, feeding, mechanical positioning of the suction nozzles, pneumatic suction and other actions, two problems may be caused: one is the center of the sucked component and the center of the suction nozzle. The center does not coincide; the second is that there is an angular deviation between the pick-up position of the component and the target placement position

[0005] The minimum circumscribing rectangle method obtains the center position and deflection angle of the component by calculating the minimum circumscribing rectangle of the component. The algorithm is simple and easy to implement. In the case of uneven gray levels, the calculated rectangle is not the ideal minimum circumscribed rectangle of the component, which affects the detection accuracy

[0006] The least squares straight line fitting method obtains the deflection angle of the component by directly performing the least squares straight line fitting on the four sides or the long edge of the component. This method is simple and efficient, but because the least squares fitting straight line must satisfy all edge points to The square sum of the distances of the straight line is the smallest, and the direct fitting method does not consider the constraints of opposite sides of the rectangular component being parallel to each other, the constraints of the leading sides being perpendicular to each other, and the influence of rough errors such as edge outliers. For components with uneven edges, foreign objects, In the case of contamination, uneven gray scale, etc., the edge outliers occupy a large proportion in the straight line fitting, which will cause inaccurate fitting of the straight line, deviate from the correct edge of the component, and affect the accuracy of the final component center positioning and angle detection

Moreover, in the existing straight line fitting method, the straight line equation all adopts the representation of f(x)=kx+b. This method defaults to a straight line that must have a slope, which is perpendicular to the x axis and has no slope (k is infinite). does not apply

In the image, straight lines may appear at any position, and using the above-mentioned straight line equation representation will inevitably lead to loopholes in algorithm processing, which will have a serious impact on the accurate acquisition of the target position

[0007] In the least squares straight line fitting method in the existing method, the straight line equation adopted is f(x)=kx+b expression, and the fitting process does not consider the edge outliers to directly fit, which greatly affects the fitting the accuracy of

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