PCB Layout Detection Using Eucledian Distance Algorithm
Keywords:
layout, euclidean, simlarityAbstract
In the image identification process, the determination of geometric coordinate transformations must be in line with the
two images. To identify the tested image, the size of similarity is defined by the alignment quality of these two images,
which measures the similarity between the tested and the fixed image. So that to detect PCB layout, it also be determined
by matching the PCB image reference feature with the tested PCB image based on differences in the imaging conditions
result. Ideally, a good similarity measurement has almost a zero deferent value and a larger value for different images.
Therefore, the Eucledian distance algorithm is proposed in this paper to detect similarity among PCBs layout with 15
training image and 30 tested images samples. Each training image has a varying reduction quality of image. From the
simulation results can be concluded that this algorithm can be used in a detecting similarity of PCB layout
References
R. C. Gonzalez and R. E. Woods (2002). “Digital Image Processing,” 2nd ed, USA: Prentice Hall, pp. 594.
Anoop K. P, Sarath N.S, Sasi Kumar V. V.( 2015). “A Review of PCB Defect Detection Using Image Processing,” International Journal of Engineering and Innovative Technology (IJEIT) Volume 4, Issue 11.
A. S.H Indera Putera, Z.Ibrahim (2012). “Printed Circuit Board Defect Detection Using Mathematical Morphology and MATLAB Image Processing Tools,” Universiti Teknologi MARA, 40450 Shah Alam, Selangor Malaysia, vol. 5, pp. 359–363.
Y. K. Chomsuwan, S. Yamada and M. Iwahara (2007).‟ Improvement on Defect Detection Performance of PCB Inspection Based on ECT Technique with Multi-SV-GMR Sensor,” IEEE Transaction on Magnetics, vol. 43, no. 6.
H. Indera Putera, Syahrul Fahmi Dzafaruddin (2012).“Matlab based defect detection and classification of printed circuit board,” digital information and communication technology and its applications (dictap) IEEE 2012 Second International Conference. Bangkok..
U. Ahmad (2005). “Pengolahan Citra Digital,”Jakarta: Graha Ilmu, hal. 14, 167. Resty Wulaningrum, S.Kom; Aeri Rachmad, ST.MT (2012). " Pengenalan Rumput Laut Menggunakan Euclidean Distance Berbasis Ekstraksi Fitur."
Dr.Eng.R.H.Sianipar,S.T,M.T,M.Eng,Herry S. Mangiri, S.T,M.Eng, I .K.Wiryajati,S.T,M.T (2013). “Matlab Untuk Pemrosesan Citra Digital,” Informatika.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Muhammad Ikhwanus, T.Iqbal Faridiansyah, Zulfikar
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Copyright Notice
Authors published in this journal agree to the following terms:
1. The copyright of each article is retained by the author (s).
2. The author grants the journal the first publication rights with the work simultaneously licensed under the Creative Commons Attribution License, allowing others to share the work with an acknowledgment of authorship and the initial publication in this journal.
3. Authors may enter into separate additional contractual agreements for the non-exclusive distribution of published journal versions of the work (for example, posting them to institutional repositories or publishing them in a book), with acknowledgment of their initial publication in this journal.
4. Authors are permitted and encouraged to post their work online (For example in the Institutional Repository or on their website) before and during the submission process, as this can lead to productive exchanges, as well as earlier and larger citations of published work.
5. Articles and all related material published are distributed under a Creative Commons Attribution-ShareAlike 4.0 International License.
