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Proceedings ArticleDOI

Automatic visual inspection of PCB using CAD information

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TLDR
In this article, the reference image is obtained from a CAD file and the inspection image is the captured image of the PCB which is obtained during image acquisition and is threshold to find the defects.
Abstract
A PCB is a thin board made of fiberglass with electrical wires printed onto the board, connecting the central processor to other components on the board For inspecting the PCB, the image of the bare PCB is captured and visually inspected to find the defects In this paper we propose a system where the reference image is obtained from a CAD file The inspection image is the captured image of the PCB which is obtained during image acquisition and is threshold To find the defects, portion of the reference image is selected and cropped By template matching the same portion is obtained from the inspection image The image subtraction is performed From the subtracted image the defects are identified The defects are extracted by feature extraction method and by shape analysis the standard defects are colored and displayed

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Citations
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Journal ArticleDOI

Unknown defect detection for printed circuit board based on multi-scale deep similarity measure method

TL;DR: A multi-layer deep feature fusion method to calculate the similarity between template and defective circuit board and Experimental results show that the proposed model has better performance in detecting and locating unknown defects in bare PCB images than traditional similarity measurement methods.
Book ChapterDOI

ANN diagnosis for defect detection and classification in two-layer printed circuit boards using supervised back-propagation algorithm

TL;DR: This work makes use of Artificial Neural Network (ANN) to visually inspect and classify the defect found in two-layer Printed Circuit Boards (PCBs) and trained and tested the data for pattern recognition using C language.

Automatic Identification of Printed Circuit Board Vias based on YOLO Algorithm

TL;DR: In this article , an automatic via identification model based on YOLO algorithm is developed to help engineers quickly locate the via on the section image of a multi-layer PCB which is necessary for subsequent processing.
Proceedings ArticleDOI

Automatic Identification of Printed Circuit Board Vias based on YOLO Algorithm

TL;DR: In this paper , an automatic via identification model based on YOLO algorithm is developed to help engineers quickly locate the via on the section image of a multi-layer PCB which is necessary for subsequent processing.
References
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Journal ArticleDOI

Automated inspection of PCB components using a genetic algorithm template-matching approach

TL;DR: In this paper, the authors used the normalised cross correlation (NCC) template-matching approach and examined a method for constraining the search space to reduce computational calculations, where the search for template positions has been exhaustively and by using a genetic algorithm.
Journal ArticleDOI

Automatic optical inspection for detecting defects on printed circuit board inner layers

TL;DR: In this paper, the authors proposed an automatic optical inspection for detecting defects on the printed circuit board inner layer, which can recognize eight defect types, open, mouse bite, pinhole, missing conductor, short, spur, excess copper and missing hole.
Journal ArticleDOI

Automatic PCB inspection systems

TL;DR: In this article, the authors proposed a machine vision-based inspection system for printed circuit board (PCB) fabrication, which removes the subjective aspects and provides fast, quantitative dimensional assessments.