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15th International Conference on Pattern Recognition (ICPR'00) - Volume 4
Extraction of Relevant Information from Document Images Using Measures of Visual Attention
Barcelona, Spain
September 03-September 08
ISBN: 0-7695-0750-6
| ASCII Text | x | ||
| Gerd Maderlechner, Angela Schreyer, Peter Suda, "Extraction of Relevant Information from Document Images Using Measures of Visual Attention," Pattern Recognition, International Conference on, vol. 4, pp. 4385, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 4, 2000. | |||
| BibTex | x | ||
| @article{ 10.1109/ICPR.2000.902939, author = {Gerd Maderlechner and Angela Schreyer and Peter Suda}, title = {Extraction of Relevant Information from Document Images Using Measures of Visual Attention}, journal ={Pattern Recognition, International Conference on}, volume = {4}, year = {2000}, isbn = {0-7695-0750-6}, pages = {4385}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.902939}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Pattern Recognition, International Conference on TI - Extraction of Relevant Information from Document Images Using Measures of Visual Attention SN - 0-7695-0750-6 SP EP A1 - Gerd Maderlechner, A1 - Angela Schreyer, A1 - Peter Suda, PY - 2000 VL - 4 JA - Pattern Recognition, International Conference on ER - | |||
This paper describes an approach to attention based layout segmentation using general principles of the human visual perception to achieve this goal. The text is considered as texture in different resolution levels. A new measure of attractiveness is introduced. The segmentation is generic and not limited to specific document classes and models. The resulting regions of interest may be used for further interpretation. The overall speed of browsing and searching large volumes of scanned documents can be increased considerably.
Citation:
Gerd Maderlechner, Angela Schreyer, Peter Suda, "Extraction of Relevant Information from Document Images Using Measures of Visual Attention," icpr, vol. 4, pp.4385, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 4, 2000
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