Parameter-Free Geometric Document Layout Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recursive X-Y cut using bounding boxes of connected components
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
Mappings and metaphors in auditory displays: An experimental assessment
ACM Transactions on Applied Perception (TAP)
Performance Evaluation and Benchmarking of Six-Page Segmentation Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Transactions on Applied Perception (TAP)
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Audio or tactile feedback: which modality when?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB)
IEEE Transactions on Image Processing
EasySnap: real-time audio feedback for blind photography
UIST '10 Adjunct proceedings of the 23nd annual ACM symposium on User interface software and technology
NudgeCam: toward targeted, higher quality media capture
Proceedings of the international conference on Multimedia
A user study of visual versus sonically-enhanced interfaces for use while walking
Proceedings of the international conference on Multimedia
Facilitating photographic documentation of accessibility in street scenes
CHI '11 Extended Abstracts on Human Factors in Computing Systems
The proceedings of the 13th international ACM SIGACCESS conference on Computers and accessibility
Evaluating the benefits of real-time feedback in mobile augmented reality with hand-held devices
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms
IEEE Transactions on Image Processing
A No-Reference Image Blur Metric Based on the Cumulative Probability of Blur Detection (CPBD)
IEEE Transactions on Image Processing
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People frequently capture photos with their smartphones, and some are starting to capture images of documents. However, the quality of captured document images is often lower than expected, even when an application that performs post-processing to improve the image is used. To improve the quality of captured images before post-processing, we developed the Smart Document Capture (SmartDCap) application that provides real-time feedback to users about the likely quality of a captured image. The quality measures capture the sharpness and framing of a page or regions on a page, such as a set of one or more columns, a part of a column, a figure, or a table. Using our approach, while users adjust the camera position, the application automatically determines when to take a picture of a document to produce a good quality result. We performed a subjective evaluation comparing SmartDCap and the Android Ice Cream Sandwich (ICS) camera application; we also used raters to evaluate the quality of the captured images. Our results indicate that users find SmartDCap to be as easy to use as the standard ICS camera application. Also, images captured using SmartDCap are sharper and better framed on average than images using the ICS camera application.