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Seul M., O'Gorman L., Sammon M.J. — Practical algorithms for image analysis. Description, examples, and code
Seul M., O'Gorman L., Sammon M.J. — Practical algorithms for image analysis. Description, examples, and code

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Название: Practical algorithms for image analysis. Description, examples, and code

Авторы: Seul M., O'Gorman L., Sammon M.J.

Аннотация:

The title says it all. This book was meant to be used. It is organized around a series of transformations that are performed on an image in going from the raw, captured form to usable result. Each step is well identified so you can go directly to the part you need. The methods and routines used are the author's choices, but they give enough information so you can dig deeper if you suspect you may have special needs.
I particularly liked the illustrations. They aren't fancy coffee table illustrations but they are very clear and pointed to what is being discussed. There are many illustrations that show the effect of the procedures on actual images from a variety of fields.


Язык: en

Рубрика: Computer science/Обработка изображений/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 2000

Количество страниц: 295

Добавлена в каталог: 22.11.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
$k$ - NN problem      241
$\theta$ plot      198
A Trees      291
A(derson)V(erskii)L(andis) Trees      291
Aboav - Weaire law      237
Accumulator array      173
Adaptive techniques      111
adjacency      211
Aliasing      98 256
angle      243
Angular sorting      157
Area      145
Area of influence      156
Autocorrelation function      155
Automatic (noninteractive) enhancement      30
Average pixel value      23 249
Averaging filter      69
Axis orientations      169
B-spline      208
Band-stop filter      266
Bandpass filter      266
Bending energy      146
Bifurcation      181
Binarization      111
Binary operation      37
Binary tree      291
Blurring      64 267
Bond angles      232
Boolean      37
Boundary transformation      124
Branch points      177
Branched data structures      291
Break point      192
Butterworth filters      64 267
Cellular patterns      235
Cellular processing      121
Central-difference      83
Centroid      147
Chain code      176
Clipping      33
Closing      123
Clustered patterns      229
Clusters      242
Codewords      179
Comer points      199
Compactness      145
Composite image      37
Compression      179
Connected binary regions      132
Connected component labeling      139
Connection      243
Connectivity      120 125 161
contour      133 135
Convex hull      156
Convolution      60 280
Convolution kernel      60
Convolution theorem      282
Coordination number      230
Criterion function      114
Critical point detection      195 198
Critical points      177 197
Cross junctions      181
Cumulative angular bend      136
Cumulative distribution      230
Curvature      146 192 198
Curvature maxima      177
Curvature plot      198
Curvature points      134
Cutoff frequency      266
Cyclic convolution      61
dc      249
Delaunay triangulation      223
Dilation      123 126
Direct-space (pixel domain)      60
Discrete Fourier Transform      249
Distance statistics      230
Divide-and-conquer      256
Dynamic range      25
Edge detection      83 91
Edge linking      95
Edge map      83
Eight connectedness      161
Endpoints      181
entropy      26 293
Erosion      123 125
Euclidean distance      243
Extreme point      157
Fast Fourier Transform      252
Feature extraction      144
FFT      252
fill      129
filling      129 138
Filter length      66 270
Filter mask      60 270
Filtering      63 265
Fitting      201 206
Flat-fielding      76
Forward FFT      256
Fourier descriptors      152
Fourier space (frequency domain)      60
Fourier transformation      248
Fractal measure      242
Freeman chain code      178
Frequency domain analysis      248
Frequency domain resolution      261
Gaussian filter      71 267
Global descriptor      146
Gradient      81
Gradient image      85
Graham scan      158
Gray-scale      28
Guiding polygon      208
High-pass filtering      76 266
Higher-order interpolation      44
Histogram bin      23
Histogram equalization      30
Histogram peak      25
Histogram stretching      32
Hit-or-miss transformation      124
Holes      147
Hough domain      172
Hough transform      172
Ideal sharpening filter      64
Ideal smoothing filter      64
Image acquisition      24
Image brightness      23
Image contrast      23
Image projection profiles      169
Image signature      169
Impulse response      278 282
Integer scaling      46
Intensity distribution      30
Intensity levels      24
Interpolation      44
Invariant linear systems      278
Inverse FFT      256
Junction features      177
Kirsch filters      85
Labyrinthine patterns      210
Laplacian      81 84
Lattices      229
Lewis law      237
Line      176
line breaks      181
Line detection      172
Line features      181 185
line filters      187
Line image      176
Line structure      185
Linear data structures      289
Linear ramp      29
Linear system      278
Linked lists      289
localization      91
Loop      181
Low-pass filter      64 71 267
Magnification      46
Mapping function      32
Mask design      270
Matched detection filter      92 283
Matched line filters      185
Medial lines      160
Median filtering      72
Minimum feature size      261
Moment invariants      149
Moments      147
Morphological processing      121
Multiresolution pyramid      102
Mutual overlap      211
Nearest-neighbor (NN) problem      225
Neighborhood      120
Neighborhood averaging      60 63
Node      289
noise reduction      69
Noncontextual technique      113
Nondirectional gradient      83
Normalized central moments      147
Nyquist      285
Object recognition      129
Opening      123
Optimal thresholding      114
Ordered arrays      229
padding      260
Parallelism      211
PCC      179
Peak detection      86
Peeling      121
pixels      23
Plane partition      222
Plane-sweep      225
Polygonal networks      235
Polygonalization      192 195
Power spectrum      249
Prewitt filters      84
Principal axes      149
Profile      169
Proximity problem      224
Pruning transformation      124
Radial contour representation      136
Randomness      246
Range finding      242
Recession      123
Region coloring      139
Region detection      138
Region filling      139
Rescaling      38
Ringing distortion      64
Rotation      47
Salt-and-pepper noise      69 129
Sampling rate      261
Sampling theorem      285
Scaling      46
Segment clusters      210
Segmentation      132
self-referential structure      289
Separable kernel      61
Shape descriptors      145
Sharpening      77
Site coordination      230
Skeleton      160
Skeleton transformation      124
Smoothing      63 69 268
Soap froths      236
Sobel filters      84
Spatial filtering      28
spatial resolution      261
Speckle noise      69
Spline fit      207
Spurs      177 184
Structuring element      122
Subsampling      98
Supersampling      99
Sweep-line      225
Tangential contour representation      136
Template matching      106
Tesselation      223
Texture      246
Thin line code      185
Thinning      160
Thinning transformation      124
Threshold      111
Threshold selection      111
TLC      185
Topological charge      232 237
Topological defects      211
Topological proximity      241
Transfer function      64 282
TREE      291
Triangulation      223
Undersampling      257
Uniform filter      69
Unsharp masking      76
Vectorization      195
Vertex      223
Voronoi diagram      222
Voronoi polygon      222
Weighted average      69
Wiener filter      93 283
Wigner - Seitz cell      223
Windowing function      259
Zero crossings      81
zooming      46
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