Hengzhou Ding

Mobile Video Capture of Multi-page Documents

This paper presents a mobile application for capturing images of printed multi-page documents with a smartphone camera. With todays available document capture applications, the user has to carefully capture individual photographs of each page and assemble them into a document, leading to a cumbersome and time consuming user experience. We propose a novel approach of using video to capture multipage documents. Our algorithm automatically selects the best still images corresponding to individual pages of the document from the video. The technique combines video motion analysis, inertial sensor signals, and an image quality (IQ) prediction technique to select the best page images from the video. For the latter, we extend a previous no-reference IQ prediction algorithm to suit the needs of our video application. The algorithm has been implemented on an iPhone 4S. Individual pages are successfully extracted for a wide variety of multi-page documents. OCR analysis shows that the quality of document images produced by our app is comparable to that of standard still captures. At the same time, user studies confirm that in the majority of trials, video capture provides an experience that is faster and more convenient than multiple still captures.

Semi-automatic object geometry estimation for image personalization

Digital printing brings about a host of benefits, one of which is the ability to create short runs of variable, customized content. One form of customization that is receiving much attention lately is in photofinishing applications, whereby personalized calendars, greeting cards, and photo books are created by inserting text strings into images. It is particularly interesting to estimate the underlying geometry of the surface and incorporate the text into the image content in an intelligent and natural way. Current solutions either allow fixed text insertion schemes into preprocessed images, or provide manual text insertion tools that are time consuming and aimed only at the high-end graphic designer. It would thus be desirable to provide some level of automation in the image personalization process. We propose a semi-automatic image personalization workflow which includes two scenarios: text insertion and text replacement. In both scenarios, the underlying surfaces are assumed to be planar. A 3-D pinhole camera model is used for rendering text, whose parameters are estimated by analyzing existing structures in the image. Techniques in image processing and computer vison such as the Hough transform, the bilateral filter, and connected component analysis are combined, along with necessary user inputs. In particular, the semi-automatic workflow is implemented as an image personalization tool, which is presented in our companion paper.1 Experimental results including personalized images for both scenarios are shown, which demonstrate the effectiveness of our algorithms.

Personalized Imaging: Moving Closer to Reality

The availability of web and on-line image sharing services makes image personalization and customization a more interesting topic. Nonetheless, designing a personalized image is a time-consuming task, requiring hours of work by expert designers. Observing the potential opportunity to make the design process easier and more amenable to ordinary users, we presented a semi-automatic tool for designing personalized images in the Electronic Imaging (EI) symposium last year.1, 2 As a follow-up, we present several improvements to the original semi-automatic tool, for both text insertion and text replacement on planar surfaces. We also describe our effort in implementing the tool as a true web-based service, which eliminates the need for installation of any software or packages by the user. We believe that we have made the technology of image personalization more friendly and accessible to ordinary users.

Dual resolution two-dimensional color barcode

In this paper, a QR code is presented with a dual resolution structure. It contains a high resolution layer that is coded in luminance and is in consistency with the conventional QR code, and a low resolution layer providing additional error checking information, that is coded in chrominance and is robust to blurring. The proposed QR code is compatible to its underlying conventional black and white barcode as it can be read by their decoders. Its advantage is additional reliability when a color decoder is used. In particular, it enhances the decoding accuracy for devices such as mobile devices for barcodes printed in small sizes.

Global image analysis to determine suitability for text-based image personalization

Lately, image personalization is becoming an interesting topic. Images with variable elements such as text usually appear much more appealing to the recipients. In this paper, we describe a method to pre-analyze the image and automatically suggest to the user the most suitable regions within an image for text-based personalization. The method is based on input gathered from experiments conducted with professional designers. It has been observed that regions that are spatially smooth and regions with existing text (e.g. signage, banners, etc.) are the best candidates for personalization. This gives rise to two sets of corresponding algorithms: one for identifying smooth areas, and one for locating text regions. Furthermore, based on the smooth and text regions found in the image, we derive an overall metric to rate the image in terms of its suitability for personalization (SFP).

Text replacement on cylindrical surfaces: a semi-automatic approach

Image-based customization that incorporates personalized text strings into photorealistic images in a natural and appealing way has been of great interest lately. We describe a semi-automatic approach for replacing text on cylindrical surfaces in images of natural scenes or objects. The user is requested to select a boundary for the existing text and align a pair of edges for the sides of the cylinder. The algorithm erases the existing text, and instantiates a 3-D cylinder forward projection model to render the new text. The parameters of the forward projection model are estimated by optimizing a carefully designed cost function. Experimental results show that the text-replaced images look natural and appealing.