A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real time image enhancement for both text and color photo images
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 1)-Volume 1 - Volume 1
CamWorks: A Video-Based Tool for Efficient Capture from Paper Source Documents
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Progress in Camera-Based Document Image Analysis
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Towards automatic sign translation
HLT '01 Proceedings of the first international conference on Human language technology research
Grouping using factor graphs: an approach for finding text with a camera phone
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
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With increasing resolution of cameras on mobile devices and their computing capacity, camera-based document processing becomes more attractive. However, there are several unique challenges, one of which is defocus. It is common that a camera-captured image is blurred by variable amount of location-dependent defocus. To improve image quality, we developed a novel method to adaptively deblur camera-based document images. In this method, sub-images of interest are first extracted from the captured image, and a point-spread function is derived for each sub-image by analyzing the gradient information along edges. Then the sub-image is deblurred by its local point-spread function. Preliminary experimental results indicate that the proposed adaptive deblurring method significantly improves focusing quality as evaluated by both human observers and objective focus measures compared with single-PSF deblurring.