Graph-based locality-sensitive circuit sketch recognizer

Abstract

The understanding of circuit diagram is very important for the study of electrical engineering. Existing circuit diagram simulation tools are mostly based on GUI interface and rely on users to click or drag icons with mouse, which requires them to be familiar with the software and distracts a great deal of their attention from the circuit diagram itself. Although a lot of previous works have devoted to designing algorithmic solution to recognize hand-drawn circuit diagrams automatically, there still exists strict constraints on users’ drawing habits and stroke orders. In order to address these inconveniences, this paper proposes a novel sketch recognition algorithm named LS4D. It uses graph to model the input strokes and their relationships, and leverages cycles by local strokes to detect some circuit components. Theoretical derivations have demonstrated that LS4D can efficiently recognize diagrams with different drawing styles and arbitrary stroke orders. To furthermore illustrate the practical value of the proposed approach, we construct a prototype of pen-based circuit diagram system based on LS4D, which enables users to draw circuit diagrams directly on the digital screen without any other restriction. An experiment of 158 samples collected from 17 users is conducted on the designed platform. Our approach has achieved 93.04% recognition accuracy and overall 4.53 from a 5-scale user satisfaction rating, which outperforms previous state-of-the-art methods numerically. It is shown that the same approach can also be generalized to many other sketch recognition applications with minor modifications. To facilitate future researches and applications, we publish our source code, model, and training data at https://github.com/Huage001/ Graph-Based-Circuit-Painter.