Graphic Symbol Recognition using Graph Based Signature and Bayesian Network Classifier

Details Graphic Symbol Recognition using Graph Based Signature and Bayesian Network Classifier Graphic Symbol Recognition using Graph Based Signature and Bayesian Network Classifier

2010-04-30

arxiv.org/abs/1004.5424v1

Computer Science

Computer Vision and Pattern Recognition

5 pages, 8 figures, Tenth International Conference on Document Analysis and Recognition (ICDAR), IEEE Computer Society, 2009,

Scientific paper

We present a new approach for recognition of complex graphic symbols in technical documents. Graphic symbol recognition is a well known challenge in the field of document image analysis and is at heart of most graphic recognition systems. Our method uses structural approach for symbol representation and statistical classifier for symbol recognition. In our system we represent symbols by their graph based signatures: a graphic symbol is vectorized and is converted to an attributed relational graph, which is used for computing a feature vector for the symbol. This signature corresponds to geometry and topology of the symbol. We learn a Bayesian network to encode joint probability distribution of symbol signatures and use it in a supervised learning scenario for graphic symbol recognition. We have evaluated our method on synthetically deformed and degraded images of pre-segmented 2D architectural and electronic symbols from GREC databases and have obtained encouraging recognition rates.

Affiliated with

Also associated with

No associations

Rating

Graphic Symbol Recognition using Graph Based Signature and Bayesian Network Classifier does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Graphic Symbol Recognition using Graph Based Signature and Bayesian Network Classifier, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Graphic Symbol Recognition using Graph Based Signature and Bayesian Network Classifier will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-386981