Technical Library: template (Page 1 of 1)

Detection of PCB Soldering Defects using Template Based Image Processing Method

Technical Library | 2021-04-15 14:49:27.0

In this study, a predefined template-based image processing system is proposed to automatically detect of PCB soldering defects that negatively affect circuit operation. The proposed system consists of a scaled inspection structure, a camera, an image processing algorithm merged with Fuzzy and template guided inspection process. The prototype is produced using a plastic material, depending on the focal length of the camera and the PCB size. Image processing step comprises two steps. Firstly, solder joints are determined and boxed using Fuzzy C-means clustering algorithm.

Selcuk University

Maintenance Policies and Procedures

Technical Library | 2020-03-08 11:35:53.0

A sample for Larry Bush's Maintenance Policies and Procedures - 2nd Edition (A 415-page book in PDF format. Those who purchase also receive 150 support files in editable format to customize and use as samples and templates.)

Business Industrial Network

Automated Inspection Of PCB Components Using A Genetic Algorithm Template-Matching Approach

Technical Library | 2021-04-15 14:44:20.0

Automated inspection of surface mount PCB boards is a requirement to assure quality and to reduce manufacturing scrap costs and rework. This paper investigates methodologies for locating and identifying multiple objects in images used for surface mount device inspection. One of the main challenges for surface mount device inspection is component placement inspection.

Springer-Verlag

A Printed Circuit Board Inspection System With Defect Classification Capability

Technical Library | 2013-08-15 13:12:11.0

An automated visual PCB inspection is an approach used to counter difficulties occurred in human’s manual inspection that can eliminates subjective aspects and then provides fast, quantitative, and dimensional assessments. In this study, referential approach has been implemented on template and defective PCB images to detect numerous defects on bare PCBs before etching process, since etching usually contributes most destructive defects found on PCBs. The PCB inspection system is then improved by incorporating a geometrical image registration, minimum thresholding technique and median filtering in order to solve alignment and uneven illumination problem. Finally, defect classification operation is employed in order to identify the source for six types of defects namely, missing hole, pin hole, underetch, short-circuit, mousebite, and open-circuit.

Universiti Teknologi Malaysia

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