Analysis and Overview of Printed Circuit Board Defect Detection Methods

Q: How many days will it take for my paper to be published?

The review time for papers is not fixed. However, if the paper is accepted and the author completes the processing charges formalities, the paper will be published within a few working days.

Q: I would like to receive a hard copy of the journal materials. Are there any additional charges?

You can log in to the author portal and pay 500 INR to receive the hard copy materials.

Snehal Ghogare; Dr Rashmi P. Sonar; Sakshi Dudhe; Suhani Harsule; Ashwini Paturkar

Analysis and Overview of Printed Circuit Board Defect Detection Methods

Authors: Snehal Ghogare, Dr Rashmi P. Sonar, Sakshi Dudhe, Suhani Harsule, Ashwini Paturkar

Unique Paper ID: 174666
Volume: 11
Issue: 11
PageNo: 869-873

Keywords: No Keywords Found

Abstract:
This paper provides an in-depth analysis and overview of various defect detection methods for Printed Circuit Boards (PCBs). A core focus is placed on feature extraction techniques, which are fundamental to accurate and reliable defect identification. The paper examines the evolution of these methods, from traditional image processing to machine learning and the now-dominant deep learning approaches, particularly Convolutional Neural Networks (CNNs). A detailed discussion of feature information is presented, encompassing handcrafted, learned (with pre-processing), and deep learning-derived features. The paper highlights how different methods represent and utilize feature information, along with recent trends and algorithms that enhance feature representation and improve PCB defect detection performance.

Download article

email to a friend

Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 11
PageNo: 869-873

Analysis and Overview of Printed Circuit Board Defect Detection Methods

Available:https://ijirt.org/article?manuscript=174666

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now