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.
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).
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.
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.
Image personalization is a widely used technique in personalized marketing,1 in which a vendor attempts to
promote new products or retain customers by sending marketing collateral that is tailored to the customers'
demographics, needs, and interests. With current solutions of which we are aware such as XMPie,2 DirectSmile,3
and AlphaPicture,4 in order to produce this tailored marketing collateral, image templates need to be created
manually by graphic designers, involving complex grid manipulation and detailed geometric adjustments. As
a matter of fact, the image template design is highly manual, skill-demanding and costly, and essentially the
bottleneck for image personalization.
We present a semi-automatic image personalization tool for designing image templates. Two scenarios are
considered: text insertion and text replacement, with the text replacement option not offered in current solutions.
The graphical user interface (GUI) of the tool is described in detail. Unlike current solutions, the tool renders
the text in 3-D, which allows easy adjustment of the text. In particular, the tool has been implemented in Java,
which introduces flexible deployment and eliminates the need for any special software or know-how on the part
of the end user.
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.