Moments and Moment Invariants in Pattern Recognition (PDF)

Moments as projections of an image's intensity onto a proper
polynomial basis can be applied to many different aspects of image
processing. These include invariant pattern recognition, image
normalization, image registration, focus/ defocus measurement, and
watermarking. This book presents a survey of both recent and
traditional image analysis and pattern recognition methods, based
on image moments, and offers new concepts of invariants to linear
filtering and implicit invariants. In addition to the theory,
attention is paid to efficient algorithms for moment computation in
a discrete domain, and to computational aspects of orthogonal
moments. The authors also illustrate the theory through practical
examples, demonstrating moment invariants in real applications
across computer vision, remote sensing and medical imaging.



Key features:



* Presents a systematic review of the basic definitions and
properties of moments covering geometric moments and complex
moments.

* Considers invariants to traditional transforms -
translation, rotation, scaling, and affine transform - from a new
point of view, which offers new possibilities of designing optimal
sets of invariants.

* Reviews and extends a recent field of invariants with respect
to convolution/blurring.

* Introduces implicit moment invariants as a tool for recognizing
elastically deformed objects.

* Compares various classes of orthogonal moments (Legendre,
Zernike, Fourier-Mellin, Chebyshev, among others) and demonstrates
their application to image reconstruction from moments.

* Offers comprehensive advice on the construction of various
invariants illustrated with practical examples.

* Includes an accompanying website providing efficient numerical
algorithms for moment computation and for constructing invariants
of various kinds, with about 250 slides suitable for a graduate
university course.

Moments and Moment Invariants in Pattern Recognition is
ideal for researchers and engineers involved in pattern recognition
in medical imaging, remote sensing, robotics and computer vision.
Post graduate students in image processing and pattern recognition
will also find the book of interest.