Abstract
With the continuous development of electronic technology, automatic detection of the PCB board has become particularly important, and the key step of the detection is to identify and locate the location mark (usually it is a round). Hough transform is one of the most widely used circle detection method, but it is complex in computing and requires much resource. For these conditions, a new idea of circle detection is proposed to get the rough location of the circle with the template matching, and then the precise positioning is accomplished by an improved Hough transform which is to draw two non-parallel strings on the orientation round and the center of the circle shall locate the strings’ perpendicular intersection. Experiments show that the method is simple and effective, and can accomplish the PCB image positioning accurately.
Highlights
The methods used by the automatic detection of the Printed Circuit Board (PCB) is a computer vision positioning
A new idea of circle detection is proposed to get the rough location of the circle with the template matching, and the precise positioning is accomplished by an improved Hough transform which is to draw two non-parallel strings on the orientation round and the center of the circle shall locate the strings’ perpendicular intersection
The methods used by the automatic detection of the PCB is a computer vision positioning
Summary
The methods used by the automatic detection of the PCB is a computer vision positioning. The basic process is to set up two location mark (usually round) in the design and manufacture of the PCB, and stepper motor controlled by computer drives a camera to intake the photograph of these two signs respectively, find the center of the two circles. Circle detection mainly refers to the striking of characteristic parameters of the image of the hole or arc, such as the center coordinates and radius. The traditional methods of detection of circular feature is the Hough Transform, which uses the correspondence between image space and parameter space to transform image space to parameter space, and by a simple cumulative statistics in the parameter space to complete the inspection task (Fu & Chen, 2010). The method is simple in principle, of fast calculation, high accuracy and can meet the needs of the PCB testing occasions
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
