On-line hand-drawn electric circuit diagram recognition using 2D dynamic programming

Feng, Guorui; Viard-Gaudin, Christian; Sun, Zhengxing

doi:10.1016/j.patcog.2009.01.031

Cited by 67 publications

(34 citation statements)

References 24 publications

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“…Classification with SVM realized a classification rate of 83%. Recognition of online hand-drawn circuit diagrams is studied in [8] where the authors employ two-dimensional dynamic programming (2D-DP) technique to segment and recognize the symbols. Likewise, recognition of architectural drawings [1], flow charts [10], Mathematical expressions [2], UML diagrams [9] and free hand sketches [11] has also been investigated in a number of studies.…”

Section: Related Workmentioning

confidence: 99%

Segmentation and Recognition of Electronic Components in Hand-Drawn Circuit Diagrams

Moetesum¹,

Younus²,

Warsi³

et al. 2018

ICST Transactions on Scalable Information Systems

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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.

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Section: Related Workmentioning

confidence: 99%

Segmentation and Recognition of Electronic Components in Hand-Drawn Circuit Diagrams

Moetesum¹,

Younus²,

Warsi³

et al. 2018

ICST Transactions on Scalable Information Systems

View full text Add to dashboard Cite

show abstract

“…Second, a combination of symbol candidates best fitting the input is chosen by solving the optimization problem. The work [6] also concerns online charts but is focused on handdrawn electric circuit diagram recognition using 2D dynamic programming. The paper [7] presents another approach to hand drawn organizational diagrams that is based on Bayesian conditional random fields (BCRFs) that jointly analyzes all drawing elements in order to incorporate contextual cues.…”

Section: Related Workmentioning

confidence: 99%

Logical Structure Recognition of Diagram Images

Sas

Markowska–Kaczmar

2015

Annals of Computer Science and Information Systems

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Abstract-This document presents a method of a logical links structure recognition between elements on diagrams. The applied approach intuitively mimics a human way of recognition that relies on merging already found connectors into more complex ones. This procedure is modeled by our method where simple and obvious connectors and gradually extended to more complex structures. Each iteration may lead to modification of connectors set obtained so far. The modifications are managed by a rules set describing logical and graphical constraints that should be satisfied by the connectors structure. If the extension leads to violation of constraints defined by the rules then the modification is not carried out. In this way, the recognized diagram structure is consistent with the assumed principles. The method was experimentally validated using the set of diagrams from three domains. In conclusions, method's advantages and drawbacks are discussed.

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“…Mu ltiple techniqu es are u sed in sketch recognition to d etect or classify regu lar geom etric shapes [6][7][8], hand w riting characters [9,10], fingerprints [11], electric circu its [12,13], d iagram s [14,15], and other u ser com m and gestu res. For instance, w ith a classic linear d iscrim inator, Rubine [16] calcu lated featu res in ord er to classify single-stroke sketches as d igits, letters and basic com m and s introd u ced in a specific w ay.…”

Section: Related Workmentioning

confidence: 99%

New method to find corner and tangent vertices in sketches using parametric cubic curves approximation

Albert

Fernández-Pacheco

2013

Pattern Recognition

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Aleixos Borrás, MN. (2013). New method to find corner and tangent vertices in sketches using parametric cubic curves approximation. Pattern Recognition. 46 (5) Abstract-Some recent approaches have been presented as simple and highly accurate corner finders in the sketches including curves, which is useful to support natural human-computer interaction, but these in most cases do not consider tangent vertices (smooth points between two geometric entities, present in engineering models), what implies an important drawback in the field of design. In this article we present a robust approach based on the approximation to parametric cubic curves of the stroke for further radius function calculation in order to detect corner and tangent vertices. We have called our approach Tangent and Corner Vertices Detection (TCVD), and it works in the following way.First, corner vertices are obtained as minimum radius peaks in the discrete radius function, where radius is obtained from differences. Second, approximated piecewise parametric curves on the stroke are obtained and the analytic radius function is calculated. Then, curves are obtained from stretches of the stroke that have a small radius.Finally, the tangent vertices are found between straight lines and curves or between curves, where no corner vertices are previously located. The radius function to obtain curves is calculated from approximated piecewise curves, which is much more noise free than discrete radius calculation. Several tests have been carried out to compare our approach to that of the current best benchmarked, and the obtained results show that our approach achieves a significant accuracy even better finding corner vertices, and moreover, tangent vertices are detected with an Accuracy near to 92% and a False Positive Rate near to 2%.

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On-line hand-drawn electric circuit diagram recognition using 2D dynamic programming

Cited by 67 publications

References 24 publications

Segmentation and Recognition of Electronic Components in Hand-Drawn Circuit Diagrams

Segmentation and Recognition of Electronic Components in Hand-Drawn Circuit Diagrams

Logical Structure Recognition of Diagram Images

New method to find corner and tangent vertices in sketches using parametric cubic curves approximation

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