Research Article
Segmentation and Recognition of Electronic Components in Hand-Drawn Circuit Diagrams
@ARTICLE{10.4108/eai.13-4-2018.154478, author={Momina Moetesum and Syed Waqar Younus and Muhammad Ali Warsi and Imran Siddiqi}, title={Segmentation and Recognition of Electronic Components in Hand-Drawn Circuit Diagrams}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={5}, number={16}, publisher={EAI}, journal_a={SIS}, year={2018}, month={4}, keywords={Hand-Drawn Circuit Diagrams, HOG Descriptor, SVM.}, doi={10.4108/eai.13-4-2018.154478} }- Momina Moetesum
Syed Waqar Younus
Muhammad Ali Warsi
Imran Siddiqi
Year: 2018
Segmentation and Recognition of Electronic Components in Hand-Drawn Circuit Diagrams
SIS
EAI
DOI: 10.4108/eai.13-4-2018.154478
Abstract
This paper presents an effective technique for segmentation and recognition of electronic components from hand-drawn circuit diagrams. Segmentation is carried out by using a series of morphological operations on the binarized images of circuits and discriminating between three categories of components (closed shape, components with connected lines, disconnected components). Each segmented component is characterized by computing the Histogram of Oriented Gradients (HOG) descriptor while classification is carried out using Support Vector Machine (SVM). The system is evaluated on 100 hand-drawn circuit diagrams with a total of 350 components. A segmentation accuracy of 87.7% while a classification rate of 92% is realized demonstrating the effectiveness of the proposed technique.
Copyright © 2018 Momina Moetesum et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
