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An Image Based Performance Evaluation Method for Page Dewarping Algorithms using SIFT Features

Syed Saqib Bukhari, Faisal Shafait, Thomas Breuel

4th International Workshop on Camera-Based Document Analysis and Recognition International Workshop on Camera-Based Document Analysis and Recognition (CBDAR-11), 4th, September 22, Beijing, China , Springer , 2011
Dewarping of camera-captured document images is one the important preprocessing steps before feeding them to a document analysis system. Over the last few years, many approaches have been proposed for document image dewarping. Usually optical character recognition (OCR) based and/or feature based approaches are used for the evaluation of dewarping algorithms. OCR based evaluation is a good measure for the performance of a dewarping method on text regions, but it does not measure how well the dewarping algorithm works on the non-text regions like mathematical equations, graphics, or tables. Feature based evaluation methods, on the other hand, do not have this problem, however, they have following limitations: i) a lot of manual assistance is required for groundtruth generation, and ii) evaluation metrics are not sufficient to get meaningful information about dewarping quality. In this paper, we present an image based methodology for the performance evaluation of dewarping algorithms using SIFT features. For ground-truths, our method only requires scanned images of pages which have been captured by a camera. This paper introduces a vectorial performance evaluation score which gives comprehensive information for determining the performance of different dewarping methods. We have tested our performance evaluation methodology on the participating methods of CBDAR 2007 document image dewarping contest and illustrated the correctness of our method.

Show BibTex:

@inproceedings {
       abstract = {Dewarping of camera-captured document images
is one the important preprocessing steps before feeding them
to a document analysis system. Over the last few years, many
approaches have been proposed for document image dewarping.
Usually optical character recognition (OCR) based and/or
feature based approaches are used for the evaluation of dewarping
algorithms. OCR based evaluation is a good measure
for the performance of a dewarping method on text regions, but
it does not measure how well the dewarping algorithm works
on the non-text regions like mathematical equations, graphics,
or tables. Feature based evaluation methods, on the other
hand, do not have this problem, however, they have following
limitations: i) a lot of manual assistance is required for groundtruth
generation, and ii) evaluation metrics are not sufficient
to get meaningful information about dewarping quality. In
this paper, we present an image based methodology for the
performance evaluation of dewarping algorithms using SIFT
features. For ground-truths, our method only requires scanned
images of pages which have been captured by a camera.
This paper introduces a vectorial performance evaluation score
which gives comprehensive information for determining the
performance of different dewarping methods. We have tested
our performance evaluation methodology on the participating
methods of CBDAR 2007 document image dewarping contest
and illustrated the correctness of our method.},
       number = {}, 
       month = {9}, 
       year = {2011}, 
       title = {An Image Based Performance Evaluation Method for Page Dewarping Algorithms using SIFT Features}, 
       journal = {}, 
       volume = {}, 
       pages = {}, 
       publisher = {Springer}, 
       author = {Syed Saqib Bukhari, Faisal Shafait, Thomas Breuel}, 
       keywords = {Performance Evaluation, Dewarping, Camera- Captured Document Images, SIFT},
       url = {http://www.dfki.de/web/forschung/publikationen/renameFileForDownload?filename=Bukhari-Dewarping-Evaluation-CBDAR11.pdf&file_id=uploads_1188}
}