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.
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