Hand drawn optical circuitrRecognition

Rabbani, Mahdi and Reza Khoshkangini and Nagendraswamy, H. S. and Mauro Conti (2016) Hand drawn optical circuitrRecognition. Procedia Computer Science, 84. 41 - 48.

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Abstract

Electrical diagram is foundation of studies in electrical science. A circuit diagram convey many information about the system. Behind any device there are plenty of electrical ingredients which perform their specific tasks, today all the electrical software tools failed to effectively convert the information automatically from a circuit image diagram to digital form. Hence electrical engineers should manually enter all information into computers, and this process takes time and bring errors with high probability. Moreover, when the diagram is hand drawn, the problem is more complicated for any electrical analysis. Thus, in this paper we propose a new method using Artificial Neural Network (ANN) to make a machine that can directly read the electrical symbols from a hand drawn circuit image. The recognition process involves two steps: first step is feature extraction using shape based features, and the second one is a classification procedure using ANN through a back propagation algorithm. The ANN was trained and tested with different hand drawn electrical images. The results show that our proposal is viable and brings good performances.

Item Type:	Article
Additional Information:	Proceeding of the Seventh International Conference on Intelligent Human Computer Interaction (IHCI 2015)
Uncontrolled Keywords:	Optical circuit recognition, electrical circuit, moments of image, artificial neural network, back propagation algorithm
Subjects:	D Physical Science > Computer Science
Divisions:	Department of > Computer Science
Depositing User:	Manjula P Library Assistant
Date Deposited:	14 Jun 2019 05:29
Last Modified:	14 Jun 2019 05:29
URI:	http://eprints.uni-mysore.ac.in/id/eprint/3032

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