#### Filter Results:

- Full text PDF available (7)

#### Publication Year

1994

2015

- This year (0)
- Last 5 years (1)
- Last 10 years (1)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Key Phrases

Learn More

- Stefan Lehmberg, Hans-Jürgen Winkler, Manfred K. Lang
- ICASSP
- 1996

In this paper a soft-decision approach for symbol segmentation within on-line sampled handwritten mathematical expressions is presented. Based on stroke-specific features as well as geometrical features between the strokes a symbol hypotheses net is generated. For assistance additional knowledge obtained by a symbol prerecognition stage is used. The results… (More)

- Hans-Jürgen Winkler
- ICASSP
- 1996

This paper addresses the problem of recognizing on-line sampled handwritten symbols. Within the proposed symbol recognition system based on Hidden Markov Models different kinds of feature extraction algorithms are used analysing on-line features as well as off-line features and combining the classification results. By conducting writer-dependent recognition… (More)

- M. Koschinski, Hans-Jürgen Winkler, Manfred K. Lang
- ICASSP
- 1995

In this paper an efficient on-line recognition system for symbols within handwritten mathematical expressions is proposed. The system is based on the generation of a symbol hypotheses net and the classification of the elements within the net. The final classification is done by calculating the most probable path through the net under regard of the stroke… (More)

- Hans-Jürgen Winkler, H. Fahrner, Manfred K. Lang
- ICASSP
- 1995

In this paper an efficient system for structural analysis of handwritten mathematical expressions is proposed. To handle the problems caused by handwriting, this system is based on a soft-decision approach. This means that alternatives for the solution are generated during the analysis process if the relation between two symbols within the expression is… (More)

- Hans-Jürgen Winkler, Manfred K. Lang
- ICASSP
- 1997

This paper is concerned with the symbol segmentation and recognition task in the context of on-line sampled handwritten mathematical expressions, the first processing stage of an overall system for understanding arithmetic formulas. Within our system a statistical approach is used tolerating ambiguities within the decision stages and resolving them either… (More)

In this paper an efficient on-line recognition system for handwritten mathematical formulas is proposed. After formula preprocessing a symbol hypotheses net is generated by extracting different features for stroke unity. Each element of the symbol hypotheses net represents a possible symbol. The data of each symbol hypotheses are preprocessed and an image… (More)

This paper is focused on the symbol segmentation and recognition problem within on-line sampled handwritten expressions, the first stage of an overall system for understanding arithmetic formulas. Within our system a statistical approach is used tolerating ambiguities within the single decision stages and resolving them either automatically by additional… (More)

- ‹
- 1
- ›