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Recognition of symbols and topology in the image of a DC circuit diagram based on contours and skeletons

Scope of research presented in this paper refers to the off-line recognition and interpretation of the content that conveys images of printed or hand-drawn direct current circuit diagrams. Photographing learning materials with different quality imprints as well as under different lighting exposures may introduce a lot of noise in the image. Besides the standard noise caused by shadows and unwanted spots, common noises that introduce ambiguities into the process of symbol and circuit topology recognition are breaks on connecting lines and symbols. That is why we have designed algorithm in such a way to ensure correct recognition even in conditions of noise. Due to the mostly regular geometric shapes and relationships that define symbols and the interconnection of symbols in an electrical circuit, and the clear topology related to the existence of nodes and branches, we decided to develop a recognition method based mostly on the structural relations. To recognize symbols and topology, we use suitable geometric primitives, contours, and skeletons that can be detected in the image. The recognition method based on the structural patterns that can handle unwanted breaks and disconnections in the image of electrical circuit diagram represents the contribution of this paper.

image processing ; symbol recognition ; electrical circuit diagram ; circuit topology ; OpenCV ; contour ; skeleton

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