A New Syntactic Approach to Graphic Symbol Recognition

This paper presents a novel syntactic symbol recognition approach to the vector based symbol recognition problem. Different from existing syntactic approaches, which usually describe the geometric relations among primitives, our method formulates a new model to describe the geometric information of a primitive with respect to the whole symbol object based on mathematical analysis. The mathematical model is theoretically rotation and scale invariant and experiments show its accuracy for vector based symbol recognition.

[1]  Su Yang.  Symbol Recognition via Statistical Integration of Pixel-Level Constraint Histograms: A New Descriptor , 2005, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Kun Zhang,et al.  Symbol Recognition with Kernel Density Matching , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Narendra Ahuja,et al.  Robust Registration and Tracking Using Kernel Density Correlation , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[4]  Yuan Yan Tang,et al.  Printed Chinese Character Similarity Measurement Using Ring Projection and Distance Transform , 1998, Int. J. Pattern Recognit. Artif. Intell..

[5]  Changjun Jiang,et al.  A structural approach to recognizing incomplete graphic objects , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[6]  Jitendra Malik,et al.  Shape matching and object recognition using shape contexts , 2010, 2010 3rd International Conference on Computer Science and Information Technology.

[7]  Yan Luo,et al.  Engineering Drawings Recognition Using a Case-based Approach , 2003, ICDAR.