Online hand-sketched graphics recognition based on attributed relational graph matching

Author(s):  
Li Changhua ◽  
Yang Bing ◽  
Xie Weixin
Author(s):  
JOSEP LLADÓS ◽  
GEMMA SÁNCHEZ

Symbol recognition is a well-known challenge in the field of graphics recognition. Due to the representational power of graph structures, a number of graph-based approaches are used to answer whether a known symbol appears in a document and under which degree of confidence. In this paper, we review the particularities of graph structures representing technical drawings and we classify them in two categories, depending on whether the structure that they represent consists of prototype patterns or repetitive patterns. The recognition is then formulated in terms of graph matching or graph parsing, respectively. Since some symbols consist of two types of structures, the main contribution of this work is to propose a combined strategy. In addition, the combination of graph matching and graph parsing processes is based on a common graph structure that also involves a graph indexing mechanism. Graph nodes are classified in equivalence classes depending on their local configuration. Graph matching indexes in such equivalence classes using the information of model graph nodes as local descriptors, and then global consistency is checked using the graph edge attributes. On the other hand, representatives of equivalence classes are used as tokens of a graph grammar that guides a parsing process to recognize repetitive structures.


2012 ◽  
Vol 215-216 ◽  
pp. 270-274 ◽  
Author(s):  
Song Qiao Tao ◽  
Wei He

3D CAD model retrieval has received a lot of attentions in the academic community. Most existent methods for 3D model similarity assessment focus on component models instead of assembly models. In this paper, an assembly model similarity assessment method is presented in order to find the similar assemblies model for design reuse. First, assembly model is described as component attributed relational graph. Then, the compatibility matrix between two assemblies is calculated, which serves as the measure of their similarity. Finally, the optimal matching under the measures is calculated using Hungarian Method. Experimental results show that this method is able to support the assembly similarity evaluation.


2010 ◽  
Vol 43 (3) ◽  
pp. 914-928 ◽  
Author(s):  
Duck Hoon Kim ◽  
Il Dong Yun ◽  
Sang Uk Lee

2010 ◽  
Vol 8 (3) ◽  
pp. 31-46 ◽  
Author(s):  
Kwong-Hung Lai ◽  
Howard Leung ◽  
Zhi-Hui Hu ◽  
Jeff K.T. Tang ◽  
Yun Xu

One of the difficulties in learning Chinese characters is distinguishing similar characters. This can cause misunderstanding and miscommunication in daily life. Thus, it is important for students learning the Chinese language to be able to distinguish similar characters and understand their proper usage. In this paper, the authors propose a game style framework to train students to distinguish similar characters. A major component in this framework is the search for similar Chinese characters in the system. From the authors’ prior work, they find the similar characters by the radical information and stroke correspondence determination. This paper improves the stroke correspondence determination by using the attributed relational graph (ARG) matching algorithm that considers both the stroke and spatial relationship during matching. The experimental results show that the new proposed method is more accurate in finding similar Chinese characters. Additionally, the authors have implemented online educational games to train students to distinguish similar Chinese characters and made use of the improved matching method for creating the game content automatically.


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