Recognizing and Simulating Sketched Logic Circuits

Liwicki, Marcus; Knipping, Lars

doi:10.1007/11553939_84

Cited by 13 publications

(7 citation statements)

References 5 publications

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“…Multiple research papers have focused on recognizing digital circuits sketches based on the pen strokes while drawing the circuit draft [3,[5][6][7]12]. The SketchRead [5] system uses shape description language to describe shapes.…”

Section: Online Recognitionmentioning

confidence: 99%

“…The Sketic technique proposed in the present paper is an offline recognition platform for digital circuits; it makes the recognition more efficient and conformable because it does not rely on the sequence of strokes as in previous studies [3,[5][6][7]12]. Instead, the input to Sketic is an image of the complete drafted circuit that can be simply taken using a mobile camera.…”

Section: Online Recognitionmentioning

confidence: 99%

“…While most of the above-mentioned steps are automated using design automation tools, drafting the digital circuit and then converting it to a valid format are not automated efficiently. Several works have been proposed to automate this step [3][4][5][6][7]. The work proposed by Zamora and Eyjólfsdóttir [7] relies on the pen strokes on the computer or tablet screen to recognize the drawn digital circuit.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sketic: a machine learning-based digital circuit recognition platform

Abdel-Majeed¹,

Almousa²,

Alsalman³

et al. 2020

Turk J Elec Eng & Comp Sci

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In digital system design, digital logic circuit diagrams are built using interconnects and symbolic representations of the basic logic gates. Constructing such diagrams using free sketches is the first step in the design process.After that the circuit schematic or code has to be generated before being able to simulate the design. While most of the mentioned steps are automated using design automation tools, drafting the schematic circuit and then converting it into a valid format that can be simulated are still done manually due to the lack of robust tools that can recognize the free sketches and incorporate them into end user simulators. Hence, the goal of this paper is to construct and deploy computer simulation tools capable of understanding free sketches and incorporate them into useful simulation tools.Such a tool will be useful at both the educational and the industrial levels. Moreover, while this tool is designed to deal with sketched logic circuits, it can be generalized and applied to many other fields to convert the sketched design into a digital format. To implement this tool, we relied on the emerging machine learning and image processing concepts to make sure that the designed system is robust and accurate. Our results show that our system is able to recognize all the gates in the digital circuit with more than 95% accuracy.

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Section: Online Recognitionmentioning

confidence: 99%

Section: Online Recognitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Sketic: a machine learning-based digital circuit recognition platform

Abdel-Majeed¹,

Almousa²,

Alsalman³

et al. 2020

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

show abstract

“…For example, Fonseca et al [14] divided strokes by pause, i.e., if the user pauses for a certain time interval before drawing next stroke, the previous strokes would belong to a component and next strokes would belong to another. Liwicki et al [15] extracted independent circuit components by switching modes. These methods can certainly work yet not flexible and user-friendly enough, since they highly rely on cooperation of users.…”

Section: Related Workmentioning

confidence: 99%

Graph-Based Locality-Sensitive Circuit Sketch Recognizer

et al. 2020

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“…As mentioned before, many efforts have been done concerning the recognition of isolated symbols that are segmented explicitly by pausing [5] or by switching between different input modes [6]. For example, Rubine [7] proposed an 11<dimension feature vector to describe a single stroke.…”

Section: $ <mentioning

confidence: 99%

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

Feng

Viard-Gaudin

Sun

2009

Pattern Recognition

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9 pagesInternational audienceIn order to facilitate sketch recognition, most online existing works assume that people will not start to draw a new symbol before the current one has been finished. We propose in this paper a method that relaxes this constraint. The proposed methodology relies on a two-dimensional dynamic programming (2D-DP) technique allowing symbol hypothesis generation, which can correctly segment and recognize interspersed symbols. In addition, as discriminative classifiers usually have limited capability to reject outliers, some domain specific knowledge is included to circumvent those errors due to untrained patterns corresponding to erroneous segmentation hypotheses. With a point-level measurement, the experiment shows that the proposed novel approach is able to achieve an accuracy of more than 90 percent

show abstract

Recognizing and Simulating Sketched Logic Circuits

Cited by 13 publications

References 5 publications

Sketic: a machine learning-based digital circuit recognition platform

Sketic: a machine learning-based digital circuit recognition platform

Graph-Based Locality-Sensitive Circuit Sketch Recognizer

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

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