A Robust Algorithm for Text String Separation from Mixed Text/Graphics Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical parsing and recognition of hand-sketched diagrams
ACM SIGGRAPH 2007 courses
| Hi-index | 0.00 |
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.