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.