Vision with direction: a systematic introduction to image processing and computer vision
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Berlin[u.a.]
Springer
2006
|
| Subjects: | |
| Online Access: | Inhaltstext Inhaltsverzeichnis |
| Physical Description: | XIII, 396 S. Ill., graph. Darst. |
| ISBN: | 9783540273226 3540273220 |
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| 100 | 1 | |a Bigun, Josef |d 1961- |e Verfasser |0 (DE-588)122899113 |4 aut | |
| 245 | 1 | 0 | |a Vision with direction |b a systematic introduction to image processing and computer vision |c Josef Bigun |
| 264 | 1 | |a Berlin[u.a.] |b Springer |c 2006 | |
| 300 | |a XIII, 396 S. |b Ill., graph. Darst. | ||
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| 650 | 4 | |a Computer vision | |
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| adam_text | JOSEF BIGUN
VISION WITH DIRECTION
A SYSTEMATIC INTRODUCTIO
N
TO IMAGE PROCESSING AN
D COMPUTER VISION
WITH 146 FIGURES, INCLUDING 130 IN COLOR
SPRI
N
G
ER
CONTENTS
PART I HUMAN AND COMPUTER VISION
1 NEURONAL PATHWAYS OF VISION 3
1.1 OPTICS AND VISUAL FIELDS OF THE EYE 3
1.2 PHOTORECEPTORS OF THE RETINA 5
1.3 GANGLION CELLS OF THE RETINA AND RECEPTIVE FIELDS 7
1.4 THE OPTIC CHIASM 9
1.5 LATERAL GENICULATE NUCLEUS (LGN) 10
1.6 THE PRIMARY VISUAL CORTEX 11
1.7 SPATIAL DIRECTION, VELOCITY, AND FREQUENCY PREFERENCE 13
1.8 FACE RECOGNITION IN HUMANS 17
1.9 FURTHER READING 19
2 COLOR 21
2.1 LENS AND COLOR 21
2.2 RETINA AND COLOR 22
2.3 NEURONAL OPERATIONS AND COLOR 24
2.4 THE 1931 CIE CHROMATICITY DIAGRAM AND COLORIMETRY 26
2.5 RGB: RED, GREEN, BLUE COLOR SPACE 30
2.6 HSB: HUE, SATURATION, BRIGHTNESS COLOR SPACE 31
PART II LINEAR TOOLS OF VISION
3 DISCRETE IMAGES AND HUBERT SPACES 35
3.1 VECTOR SPACES 35
3.2 DISCRETE IMAGE TYPES, EXAMPLES 37
3.3 NORMS OF VECTORS AND DISTANCES BETWEEN POINTS 40
3.4 SCALAR PRODUCTS 44
3.5 ORTHOGONAL EXPANSION 46
3.6 TENSORS AS HUBERT SPACES 48
3.7 SCHWARTZ INEQUALITY, ANGLES AND SIMILARITY OF IMAGES 53
X CONTENTS
4 CONTINUOUS FUNCTIONS AND HUBERT SPACES 57
4.1 FUNCTIONS AS A VECTOR SPACE 57
4.2 ADDITION AND SCALING IN VECTOR SPACES OF FUNCTIONS 58
4.3 A SCALAR PRODUCT FOR VECTOR SPACES OF FUNCTIONS 59
4.4 ORTHOGONALITY 59
4.5 SCHWARTZ INEQUALITY FOR FUNCTIONS, ANGLES 60
5 FINITE EXTENSION OR PERIODIC FUNCTIONS-FOURIER COEFFICIENTS 61
5.1 THE FINITE EXTENSION FUNCTIONS VERSUS PERIODIC FUNCTIONS 61
5.2 FOURIER COEFFICIENTS (FC) 62
5.3 (PARSEVAL-PLANCHEREL) CONSERVATION OF THE SCALAR PRODUCT 65
5.4 HERMITIAN SYMMETRY OF THE FOURIER COEFFICIENTS 67
6 FOURIER TRANSFORM-INFINITE EXTENSION FUNCTIONS 69
6.1 THE FOURIER TRANSFORM (FT) 69
6.2 SAMPLED FUNCTIONS AND THE FOURIER TRANSFORM 72
6.3 DISCRETE FOURIER TRANSFORM (DFT) 79
6.4 CIRCULAR TOPOLOGY OF DFT 82
7 PROPERTIES OF THE FOURIER TRANSFORM 85
7.1 THE DIRAC DISTRIBUTION 85
7.2 CONSERVATION OF THE SCALAR PRODUCT 88
7.3 CONVOLUTION, FT, AND THE 5 90
7.4 CONVOLUTION WITH SEPARABLE FILTERS 94
7.5 POISSON SUMMATION FORMULA, THE COMB 95
7.6 HERMITIAN SYMMETRY OF THE FT 98
7.7 CORRESPONDENCES BETWEEN FC, DFT, AND FT 99
8 RECONSTRUCTION AND APPROXIMATION 103
8.1 CHARACTENSTIC AND INTERPOLATION FUNCTIONS IN N DIMENSIONS 103
8.2 SAMPLING BAND-PRESERVING LINEAR OPERATORS 109
8.3 SAMPLING BAND-ENLARGING OPERATORS 114
9 SCALES AND FREQUENCY CHANNELS 119
9.1 SPECTRAL EFFECTS OF DOWN- AND UP-SAMPLING 119
9.2 THE GAUSSIAN AS INTERPOLATOR 125
9.3 OPTIMIZING THE GAUSSIAN INTERPOLATOR 127
9.4 EXTENDING GAUSSIANS TO HIGHER DIMENSIONS 130
9.5 GAUSSIAN AND LAPLACIAN PYRAMIDS 134
9.6 DISCRETE LOCAL SPECTRUM, GABOR FILTERS 136
9.7 DESIGN OF GABOR FILTERS ON NONREGULAR GRIDS 142
9.8 FACE RECOGNITION BY GABOR FILTERS, AN APPLICATION 146
CONTENTS XI
PART III VISION OF SINGLE DIRECTUM
10 DIRECTION IN 2D 153
10.1 LINEARLY SYMMETRIE IMAGES 153
10.2 REAL AND COMPLEX MOMENTS IN 2D 163
10.3 THE STRUCTURE TENSOR IN 2D 164
10.4 THE COMPLEX REPRESENTATION OF THE STRUCTURE TENSOR 168
10.5 LINEAR SYMMETRY TENSOR: DIRECTIONAL DOMINANCE 171
10.6 BALANCED DIRECTION TENSOR: DIRECTIONAL EQUILIBRIUM 171
10.7 DECOMPOSING THE COMPLEX STRUCTURE TENSOR 173
10.8 DECOMPOSING THE REAL-VALUED STRUCTURE TENSOR 175
10.9 CONVENTIONAL CORNERS AND BALANCED DIRECTIONS 176
10.10 THE TOTAL LEAST SQUARES DIRECTION AND TENSORS 177
10.11 DISCRETE STRUCTURE TENSOR BY DIRECT TENSOR SAMPLING 180
10.12 APPLICATION EXAMPLES 186
10.13 DISCRETE STRUCTURE TENSOR BY SPECTRUM SAMPLING (GABOR) 187
10.14 RELATIONSHIP OF THE TWO DISCRETE STRUCTURE TENSORS 196
10.15 HOUGH TRANSFORM OF LINES 199
10.16 THE STRUCTURE TENSOR AND THE HOUGH TRANSFORM 202
10.17 APPENDIX 205
11 DIRECTION IN CURVILINEAR COORDINATES 209
11.1 CURVILINEAR COORDINATES BY HARMONIE FUNCTIONS 209
11.2 LIE OPERATORS AND COORDINATE TRANSFORMATIONS 213
11.3 THE GENERALIZED STRUCTURE TENSOR (GST) 215
11.4 DISCRETE APPROXIMATION OF GST 221
11.5 THE GENERALIZED HOUGH TRANSFORM (GHT) 224
11.6 VOTING IN GST AND GHT 226
11.7 HARMONIE MONOMIALS 228
11.8 STEERABILITY OF HARMONIE MONOMIALS 230
11.9 SYMMETRY DERIVATIVES AND GAUSSIANS 231
11.10 DISCRETE GST FOR HARMONIE MONOMIALS 233
11.11 EXAMPLES OF GST APPLICATIONS 236
11.12 FURTHER READING 238
11.13 APPENDIX 240
12 DIRECTION IN IVD, MOTION AS DIRECTION 245
12.1 THE DIRECTION OF HYPERPLANES AND THE INERTIA TENSOR 245
12.2 THE DIRECTION OF LINES AND THE STRUCTURE TENSOR 249
12.3 THE DECOMPOSITION OF THE STRUCTURE TENSOR 252
12.4 BASIC CONCEPTS OF IMAGE MOTION 255
12.5 TRANSLATING LINES 258
12.6 TRANSLATING POINTS 259
12.7 DISCRETE STRUCTURE TENSOR BY TENSOR SAMPLING IN JVD 263
XII CONTENTS
12.8 AFFINE MOTION BY THE STRUCTURE TENSOR IN TD 267
12.9 MOTION ESTIMATION BY DIFFERENTIALS IN TWO FRAMES 270
12.10 MOTION ESTIMATION BY SPATIAL CORRELATION 272
12.11 FURTHER READING 274
12.12 APPENDIX 275
13 WORLD GEOMETRY BY DIRECTION IN N DIMENSIONS 277
13.1 CAMERA COORDINATES AND INTRINSIC PARAMETERS 277
13.2 WORLD COORDINATES 283
13.3 INTRINSIC AND EXTRINS
K MATRICES BY CORRESPONDENCE 287
13.4 RECONSTRUCTING 3D BY STEREO, TRIANGULATION 293
13.5 SEARCHING FOR CORRESPONDING POINTS IN STEREO 300
13.6 THE FUNDAMENTAL MATRIX BY CORRESPONDENCE 305
13.7 FURTHER READING 307
13.8 APPENDIX 308
PART IV VISION OF MULTIPLE DIRECTIONS
14 GROUP DIRECTION AND IV-FOLDED SYMMETRY 311
14.1 GROUP DIRECTION OF REPEATING LINE PATTERNS 311
14.2 TEST IMAGES BY LOGARITHMIC SPIRALS 314
14.3 GROUP DIRECTION TENSOR BY COMPLEX MOMENTS 315
14.4 GROUP DIRECTION AND THE POWER SPECTRUM 318
14.5 DISCRETE GROUP DIRECTION TENSOR BY TENSOR SAMPLING 320
14.6 GROUP DIRECTION TENSORS AS TEXTURE FEATURES 324
14.7 FURTHER READING 326
PART V GROUPING, SEGMENTATION, AND REGION DESCRIPTION
15 REDUCING THE DIMENSION OF FEATURES 329
15.1 PRINCIPAL COMPONENT ANALYSIS (PCA) 329
15.2 PCA FOR RARE OBSERVATIONS IN LARGE DIMENSIONS 335
15.3 SINGULAR VALUE DECOMPOSITION (SVD) 338
16 GROUPING AND UNSUPERVISED REGION SEGREGATION 341
16.1 THE UNCERTAINTY PRINCIPLE AND SEGMENTATION 341
16.2 PYRAMID BUILDING 344
16.3 CLUSTERING IMAGE FEATURES-PERCEPTUAL GROUPING 345
16.4 FUZZY C-MEANS CLUSTERING ALGORITHM 347
16.5 ESTABLISHING THE SPATIAL CONTINUITY 348
16.6 BOUNDARY REFINEMENT BY ORIENTED BUTTERFLY FILTERS 351
16.7 TEXTURE GROUPING AND BOUNDARY ESTIMATION INTEGRATION 354
16.8 FURTHER READING 35G
CONTENT
S XII
I
17 REGION AND BOUNDARY DESCRIPTORS 359
17.1 MORPHOLOGICAL FILTERING OF REGIONS 359
17.2 CONNECTED COMPONENT LABELLING 364
17.3 ELEMENTARY SHAPE FEATURES 366
17.4 MOMENL-BASED DESCRIPTION OF SHAPE 368
17.5 FOURIER DESCRIPTORS AND SHAPE OF A REGION 371
18 CONCLUDING REMARKS 377
REFERENCES 379
INDEX 391
|
| adam_txt |
JOSEF BIGUN
VISION WITH DIRECTION
A SYSTEMATIC INTRODUCTIO
N
TO IMAGE PROCESSING AN
D COMPUTER VISION
WITH 146 FIGURES, INCLUDING 130 IN COLOR
SPRI
N
G
ER
CONTENTS
PART I HUMAN AND COMPUTER VISION
1 NEURONAL PATHWAYS OF VISION 3
1.1 OPTICS AND VISUAL FIELDS OF THE EYE 3
1.2 PHOTORECEPTORS OF THE RETINA 5
1.3 GANGLION CELLS OF THE RETINA AND RECEPTIVE FIELDS 7
1.4 THE OPTIC CHIASM 9
1.5 LATERAL GENICULATE NUCLEUS (LGN) 10
1.6 THE PRIMARY VISUAL CORTEX 11
1.7 SPATIAL DIRECTION, VELOCITY, AND FREQUENCY PREFERENCE 13
1.8 FACE RECOGNITION IN HUMANS 17
1.9 FURTHER READING 19
2 COLOR 21
2.1 LENS AND COLOR 21
2.2 RETINA AND COLOR 22
2.3 NEURONAL OPERATIONS AND COLOR 24
2.4 THE 1931 CIE CHROMATICITY DIAGRAM AND COLORIMETRY 26
2.5 RGB: RED, GREEN, BLUE COLOR SPACE 30
2.6 HSB: HUE, SATURATION, BRIGHTNESS COLOR SPACE 31
PART II LINEAR TOOLS OF VISION
3 DISCRETE IMAGES AND HUBERT SPACES 35
3.1 VECTOR SPACES 35
3.2 DISCRETE IMAGE TYPES, EXAMPLES 37
3.3 NORMS OF VECTORS AND DISTANCES BETWEEN POINTS 40
3.4 SCALAR PRODUCTS 44
3.5 ORTHOGONAL EXPANSION 46
3.6 TENSORS AS HUBERT SPACES 48
3.7 SCHWARTZ INEQUALITY, ANGLES AND SIMILARITY OF IMAGES 53
X CONTENTS
4 CONTINUOUS FUNCTIONS AND HUBERT SPACES 57
4.1 FUNCTIONS AS A VECTOR SPACE 57
4.2 ADDITION AND SCALING IN VECTOR SPACES OF FUNCTIONS 58
4.3 A SCALAR PRODUCT FOR VECTOR SPACES OF FUNCTIONS 59
4.4 ORTHOGONALITY 59
4.5 SCHWARTZ INEQUALITY FOR FUNCTIONS, ANGLES 60
5 FINITE EXTENSION OR PERIODIC FUNCTIONS-FOURIER COEFFICIENTS 61
5.1 THE FINITE EXTENSION FUNCTIONS VERSUS PERIODIC FUNCTIONS 61
5.2 FOURIER COEFFICIENTS (FC) 62
5.3 (PARSEVAL-PLANCHEREL) CONSERVATION OF THE SCALAR PRODUCT 65
5.4 HERMITIAN SYMMETRY OF THE FOURIER COEFFICIENTS 67
6 FOURIER TRANSFORM-INFINITE EXTENSION FUNCTIONS 69
6.1 THE FOURIER TRANSFORM (FT) 69
6.2 SAMPLED FUNCTIONS AND THE FOURIER TRANSFORM 72
6.3 DISCRETE FOURIER TRANSFORM (DFT) 79
6.4 CIRCULAR TOPOLOGY OF DFT 82
7 PROPERTIES OF THE FOURIER TRANSFORM 85
7.1 THE DIRAC DISTRIBUTION 85
7.2 CONSERVATION OF THE SCALAR PRODUCT 88
7.3 CONVOLUTION, FT, AND THE 5 90
7.4 CONVOLUTION WITH SEPARABLE FILTERS 94
7.5 POISSON SUMMATION FORMULA, THE COMB 95
7.6 HERMITIAN SYMMETRY OF THE FT 98
7.7 CORRESPONDENCES BETWEEN FC, DFT, AND FT 99
8 RECONSTRUCTION AND APPROXIMATION 103
8.1 CHARACTENSTIC AND INTERPOLATION FUNCTIONS IN N DIMENSIONS 103
8.2 SAMPLING BAND-PRESERVING LINEAR OPERATORS 109
8.3 SAMPLING BAND-ENLARGING OPERATORS 114
9 SCALES AND FREQUENCY CHANNELS 119
9.1 SPECTRAL EFFECTS OF DOWN- AND UP-SAMPLING 119
9.2 THE GAUSSIAN AS INTERPOLATOR 125
9.3 OPTIMIZING THE GAUSSIAN INTERPOLATOR 127
9.4 EXTENDING GAUSSIANS TO HIGHER DIMENSIONS 130
9.5 GAUSSIAN AND LAPLACIAN PYRAMIDS 134
9.6 DISCRETE LOCAL SPECTRUM, GABOR FILTERS 136
9.7 DESIGN OF GABOR FILTERS ON NONREGULAR GRIDS 142
9.8 FACE RECOGNITION BY GABOR FILTERS, AN APPLICATION 146
CONTENTS XI
PART III VISION OF SINGLE DIRECTUM
10 DIRECTION IN 2D 153
10.1 LINEARLY SYMMETRIE IMAGES 153
10.2 REAL AND COMPLEX MOMENTS IN 2D 163
10.3 THE STRUCTURE TENSOR IN 2D 164
10.4 THE COMPLEX REPRESENTATION OF THE STRUCTURE TENSOR 168
10.5 LINEAR SYMMETRY TENSOR: DIRECTIONAL DOMINANCE 171
10.6 BALANCED DIRECTION TENSOR: DIRECTIONAL EQUILIBRIUM 171
10.7 DECOMPOSING THE COMPLEX STRUCTURE TENSOR 173
10.8 DECOMPOSING THE REAL-VALUED STRUCTURE TENSOR 175
10.9 CONVENTIONAL CORNERS AND BALANCED DIRECTIONS 176
10.10 THE TOTAL LEAST SQUARES DIRECTION AND TENSORS 177
10.11 DISCRETE STRUCTURE TENSOR BY DIRECT TENSOR SAMPLING 180
10.12 APPLICATION EXAMPLES 186
10.13 DISCRETE STRUCTURE TENSOR BY SPECTRUM SAMPLING (GABOR) 187
10.14 RELATIONSHIP OF THE TWO DISCRETE STRUCTURE TENSORS 196
10.15 HOUGH TRANSFORM OF LINES 199
10.16 THE STRUCTURE TENSOR AND THE HOUGH TRANSFORM 202
10.17 APPENDIX 205
11 DIRECTION IN CURVILINEAR COORDINATES 209
11.1 CURVILINEAR COORDINATES BY HARMONIE FUNCTIONS 209
11.2 LIE OPERATORS AND COORDINATE TRANSFORMATIONS 213
11.3 THE GENERALIZED STRUCTURE TENSOR (GST) 215
11.4 DISCRETE APPROXIMATION OF GST 221
11.5 THE GENERALIZED HOUGH TRANSFORM (GHT) 224
11.6 VOTING IN GST AND GHT 226
11.7 HARMONIE MONOMIALS 228
11.8 "STEERABILITY" OF HARMONIE MONOMIALS 230
11.9 SYMMETRY DERIVATIVES AND GAUSSIANS 231
11.10 DISCRETE GST FOR HARMONIE MONOMIALS 233
11.11 EXAMPLES OF GST APPLICATIONS 236
11.12 FURTHER READING 238
11.13 APPENDIX 240
12 DIRECTION IN IVD, MOTION AS DIRECTION 245
12.1 THE DIRECTION OF HYPERPLANES AND THE INERTIA TENSOR 245
12.2 THE DIRECTION OF LINES AND THE STRUCTURE TENSOR 249
12.3 THE DECOMPOSITION OF THE STRUCTURE TENSOR 252
12.4 BASIC CONCEPTS OF IMAGE MOTION 255
12.5 TRANSLATING LINES 258
12.6 TRANSLATING POINTS 259
12.7 DISCRETE STRUCTURE TENSOR BY TENSOR SAMPLING IN JVD 263
XII CONTENTS
12.8 AFFINE MOTION BY THE STRUCTURE TENSOR IN TD 267
12.9 MOTION ESTIMATION BY DIFFERENTIALS IN TWO FRAMES 270
12.10 MOTION ESTIMATION BY SPATIAL CORRELATION 272
12.11 FURTHER READING 274
12.12 APPENDIX 275
13 WORLD GEOMETRY BY DIRECTION IN N DIMENSIONS 277
13.1 CAMERA COORDINATES AND INTRINSIC PARAMETERS 277
13.2 WORLD COORDINATES 283
13.3 INTRINSIC AND EXTRINS
K MATRICES BY CORRESPONDENCE 287
13.4 RECONSTRUCTING 3D BY STEREO, TRIANGULATION 293
13.5 SEARCHING FOR CORRESPONDING POINTS IN STEREO 300
13.6 THE FUNDAMENTAL MATRIX BY CORRESPONDENCE 305
13.7 FURTHER READING 307
13.8 APPENDIX 308
PART IV VISION OF MULTIPLE DIRECTIONS
14 GROUP DIRECTION AND IV-FOLDED SYMMETRY 311
14.1 GROUP DIRECTION OF REPEATING LINE PATTERNS 311
14.2 TEST IMAGES BY LOGARITHMIC SPIRALS 314
14.3 GROUP DIRECTION TENSOR BY COMPLEX MOMENTS 315
14.4 GROUP DIRECTION AND THE POWER SPECTRUM 318
14.5 DISCRETE GROUP DIRECTION TENSOR BY TENSOR SAMPLING 320
14.6 GROUP DIRECTION TENSORS AS TEXTURE FEATURES 324
14.7 FURTHER READING 326
PART V GROUPING, SEGMENTATION, AND REGION DESCRIPTION
15 REDUCING THE DIMENSION OF FEATURES 329
15.1 PRINCIPAL COMPONENT ANALYSIS (PCA) 329
15.2 PCA FOR RARE OBSERVATIONS IN LARGE DIMENSIONS 335
15.3 SINGULAR VALUE DECOMPOSITION (SVD) 338
16 GROUPING AND UNSUPERVISED REGION SEGREGATION 341
16.1 THE UNCERTAINTY PRINCIPLE AND SEGMENTATION 341
16.2 PYRAMID BUILDING 344
16.3 CLUSTERING IMAGE FEATURES-PERCEPTUAL GROUPING 345
16.4 FUZZY C-MEANS CLUSTERING ALGORITHM 347
16.5 ESTABLISHING THE SPATIAL CONTINUITY 348
16.6 BOUNDARY REFINEMENT BY ORIENTED BUTTERFLY FILTERS 351
16.7 TEXTURE GROUPING AND BOUNDARY ESTIMATION INTEGRATION 354
16.8 FURTHER READING 35G
CONTENT
S XII
I
17 REGION AND BOUNDARY DESCRIPTORS 359
17.1 MORPHOLOGICAL FILTERING OF REGIONS 359
17.2 CONNECTED COMPONENT LABELLING 364
17.3 ELEMENTARY SHAPE FEATURES 366
17.4 MOMENL-BASED DESCRIPTION OF SHAPE 368
17.5 FOURIER DESCRIPTORS AND SHAPE OF A REGION 371
18 CONCLUDING REMARKS 377
REFERENCES 379
INDEX 391 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Bigun, Josef 1961- |
| author_GND | (DE-588)122899113 |
| author_facet | Bigun, Josef 1961- |
| author_role | aut |
| author_sort | Bigun, Josef 1961- |
| author_variant | j b jb |
| building | Verbundindex |
| bvnumber | BV021715527 |
| classification_rvk | ST 330 |
| ctrlnum | (OCoLC)181471205 (DE-599)BVBBV021715527 |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| format | Book |
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| id | DE-604.BV021715527 |
| illustrated | Illustrated |
| index_date | 2024-07-02T15:21:53Z |
| indexdate | 2024-07-09T20:42:21Z |
| institution | BVB |
| isbn | 9783540273226 3540273220 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-014929272 |
| oclc_num | 181471205 |
| open_access_boolean | |
| owner | DE-20 DE-634 DE-11 |
| owner_facet | DE-20 DE-634 DE-11 |
| physical | XIII, 396 S. Ill., graph. Darst. |
| publishDate | 2006 |
| publishDateSearch | 2006 |
| publishDateSort | 2006 |
| publisher | Springer |
| record_format | marc |
| spelling | Bigun, Josef 1961- Verfasser (DE-588)122899113 aut Vision with direction a systematic introduction to image processing and computer vision Josef Bigun Berlin[u.a.] Springer 2006 XIII, 396 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Computer vision Image processing Maschinelles Sehen (DE-588)4129594-8 gnd rswk-swf Maschinelles Sehen (DE-588)4129594-8 s DE-604 text/html http://deposit.dnb.de/cgi-bin/dokserv?id=2668736&prov=M&dok_var=1&dok_ext=htm Inhaltstext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014929272&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Bigun, Josef 1961- Vision with direction a systematic introduction to image processing and computer vision Computer vision Image processing Maschinelles Sehen (DE-588)4129594-8 gnd |
| subject_GND | (DE-588)4129594-8 |
| title | Vision with direction a systematic introduction to image processing and computer vision |
| title_auth | Vision with direction a systematic introduction to image processing and computer vision |
| title_exact_search | Vision with direction a systematic introduction to image processing and computer vision |
| title_exact_search_txtP | Vision with direction a systematic introduction to image processing and computer vision |
| title_full | Vision with direction a systematic introduction to image processing and computer vision Josef Bigun |
| title_fullStr | Vision with direction a systematic introduction to image processing and computer vision Josef Bigun |
| title_full_unstemmed | Vision with direction a systematic introduction to image processing and computer vision Josef Bigun |
| title_short | Vision with direction |
| title_sort | vision with direction a systematic introduction to image processing and computer vision |
| title_sub | a systematic introduction to image processing and computer vision |
| topic | Computer vision Image processing Maschinelles Sehen (DE-588)4129594-8 gnd |
| topic_facet | Computer vision Image processing Maschinelles Sehen |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=2668736&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014929272&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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