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VisionSynaptics: a system convert hand-writing and image symbol into computer symbol

Published: 24 November 2009 Publication History

Abstract

In recent years, the electronic white board and the tablet smart PC device receive more and more attraction as an important technique and wide application in human-computer interaction, such as education, entertainment and engineering application etc. In this paper, we presented a novel and intelligent symbol recognition platform, VisionSynaptics, which can convert image and handwriting symbol into computer symbol. For the single symbol recognition, our system is invariant to scaling, rotation, translation and style of drawing and for the sketch or flowchart, VisionSynaptics establishes an architecture that utilizes a number of pattern recognition tools to convert hand-drawn or image diagrams into computer graphics by segmenting the original diagram into individual components. This method generates hypothesis graphs for each component and utilizes a rule-based floor planning routine for component and symbol placement. Experiments have indicated that even novice users can effectively utilize our system to solve real engineering problems without having to know much about the underlying recognition techniques. Therefore, such system brings a new technique for human factor with that users can learn the abstract symbol, graphics and flowchart effectively and efficiently by the visual comparative learning assisted.

References

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Llados, J., Sanchez, G.: Symbol recognition by error-tolerant subgraph matching between region adjacency graphs. IEEE International Conference on Image Processing 2(10), II--49--II--52 (2003)
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Fletcher, L., Kasturi, R.: A robust algorithm for text string separation from mixed text/graphics images. IEEE Transaction on Pattern Analysis and Machine Intelligence 10(6), 910--918(1988).
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Huang, B., Kechadi, M.: An hmm-snn method for online handwriting symbol recognition II, 897--905 (2006)
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Pradhan, A., Routray, A., Behera, A.: Power quality disturbance classification employing modular wavelet network. In: Power Engineering Society General Meeting. IEEE, Los Alamitos (2006)
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Yuan, Z., Pan, H., Zhang, L.: A novel pen-based flowchart recognition system for programming teaching, pp. 55--64 (2009)
[6]
Kara, L. B., Stahovich, T. F.: Hierarchical parsing and recognition of hand-sketched diagrams. In: SIGGRAPH 2007: ACM SIGGRAPH 2007 courses, p. 17. ACM, New York (2007)

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  1. VisionSynaptics: a system convert hand-writing and image symbol into computer symbol

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      ICIS '09: Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
      November 2009
      1479 pages
      ISBN:9781605587103
      DOI:10.1145/1655925
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 24 November 2009

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      Author Tags

      1. graphics segmenting
      2. human-computer interaction
      3. intelligent system
      4. symbol recognition

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