The concept of 'shape' is at the heart of image processing and computer
vision, yet researchers still have some way to go to replicate the human
brain's ability to extrapolate meaning from the most basic of outlines.
This volume reflects the advances of the last decade, which have also
opened up tough new challenges in image processing. Today's applications
require flexible models as well as efficient, mathematically justified
algorithms that allow data processing within an acceptable timeframe.
Examining important topics in continuous-scale and discrete modeling, as
well as in modern algorithms, the book is the product of a key seminar
focused on innovations in the field. It is a thorough introduction to
the latest technology, especially given the tutorial style of a number
of chapters. It also succeeds in identifying promising avenues for
future research. The topics covered include mathematical morphology,
skeletonization, statistical shape modeling, continuous-scale shape
models such as partial differential equations and the theory of discrete
shape descriptors. Some authors highlight new areas of enquiry such as
partite skeletons, multi-component shapes, deformable shape models, and
the use of distance fields.
Combining the latest theoretical analysis with cutting-edge
applications, this book will attract both academics and engineers.