Image Processing, Analysis, and
Machine Vision
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Image Processing, Analysis, and
Machine Vision
Fourth Edition
Milan Sonka
The University of Iowa, Iowa City
Vaclav Hlavac
Czech Technical University, Prague
Roger Boyle
Prifysgol Aberystwyth, Aberystwyth
Australia • Brazil • Japan • Mexico • Singapore • United Kingdom • United States
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Image Processing, Analysis, and
Machine Vision, Fourth Edition
Milan Sonka, Vaclav Hlavac, and
Roger Boyle
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ISBN-13: 978-1-133-59360-7
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Abbreviations
1D
2D, 3D, ...
AAM
AGC
AI
ART
ASM
BBF
BBN
BRDF
B-rep
CAD
CCD
CHMM
CIE
CMOS
CMY
CONDENSATION
CRT
CSF
CSG
CT
dB
DCT
DFT
dof
DPCM
DWF
ECG
EEG
EM
FFT
FLANN
FOE
GA
one dimension(al)
two dimension(al), three dimension(al), ...
active appearance model
automatic gain control
artificial intelligence
adaptive resonance theory
active shape model
best bin first
Bayesian belief network
bi-directional reflectance distribution function
boundary representation
computer-aided design
charge-coupled device
coupled HMM
International Commission on Illumination
complementary metal-oxide semiconductor
cyan, magenta, yellow
CONditional DENSity propagATION
cathode ray tube
cerebro-spinal fluid
constructive solid geometry
computed tomography
decibel, 20 times the decimal logarithm of a ratio
discrete cosine transform
discrete Fourier transform
degrees of freedom
differential PCM
discrete wavelet frame
electro-cardiogram
electro-encephalogram
expectation-maximization
fast Fourier transform
fast library for approximate nearest neighbors
focus of expansion
genetic algorithm
Copyright 201 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
GB
GIS
GMM
GRBF
GVF
HDTV
HLS
HMM
HOG
HSI
HSL
HSV
ICA
ICP
ICRP
IHS
JPEG
Kb
KB
KLT
LBP
LCD
MAP
Mb
MB
MB, MB2
MCMC
MDL
MJPEG
MPEG
MRF
MRI
MR
MSE
MSER
ms
Giga byte = 230 bytes = 1,073,741,824 bytes
geographic information system
Gaussian mixture model
Gaussian radial basis function
gradient vector flow
high definition TV
as HSI
hidden Markov model
histogram of oriented gradients
hue, saturation, intensity
as HSI
hue, saturation, value
independent component analysis
iterative closest point algorithm
iterative closest reciprocal point algorithm
intensity, hue, saturation
Joint Photographic Experts Group
Kilo bit = 210 bits = 1,024 bits
Kilo byte = 210 bytes = 1,024 bytes
Kanade-Lucas-Tomasi (tracker)
local binary pattern
liquid crystal display
maximum a posteriori
Mega bit = 220 bits = 1,048,576 bits
Mega byte = 220 bytes = 1,048,576 bytes
Manzanera–Bernard skeletonization
Monte Carlo Markov chain
minimum description length
motion JPEG
moving picture experts group
Markov random field
magnetic resonance imaging
magnetic resonance
mean-square error
maximally stable extremal region
millisecond
Copyright 201 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
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