IST16170 Дар Жежнича П. І.

Бібліографія: сторінки 300-302 (47 назв)

Preface.....IV
Chapter 1. Custering algorithms for image processing.....1
1.1. Algorithms and criteria.....1
1.2. Clustering К-means algorithm.....10
1.3. Reducing hierarchical clustering algorithm complexity.....12
1.4. Space decomposition by multilevel segmentation.....17
1.5. З-stages clustering algorithm of hypercubes.....28
1.6. З-stages clustering algorithm for image analysis and classification.....31
1.6.1. Pattern decomposition.....35
1.6.2. Decomposition algorithm.....36
1.6.3. 4-D integral pattern features.....40
1.6.4. Application of structure features for image analysis.....43
1.7. Conclusion.....39
Chapter 2. Piecewise linear approximation.....41
2.1. Introduction to piecewise linear approximation.....41
2.2. Algorithm oi Ramer-Dougias-Packer for piecewise linear approximation.....44
2.3. Modified algorithm of Ramer-Douglas-Packer for piecewise linear approximation.....46
2.4. Method of average coefficients.....48
2.5. Chebyshev approximation method.....51
2.6. Image compression by piecewise linear approximation.....53
2.7. Investigation of piecewise-linear approximation algorithms to compress images.....56
2.8. Image compression by the Visvalingam-Whyatt algorithm.....62
2.9. Conclusion.....66
Chapter 3. Segmentation and transformation of images.....68
3.1. Segmentation by statistical features.....68
3.2. Segmentation by inclined plane.....73
3.3. Multilevel segmentation using approximation of cumulative histogram.....80
3.4. Distributed cumulative histogram.....85
3.5. Segmentation by K-means clustering.....87
3.6. Transformation of image by rotation.....95
3.7. Conclusion......104
Chapter 4. Skeletonization and clustering for defects detection in pcb images.....105
4.1. Hilditch's thinning algorithm and its application.....105
4.2. Auxiliary algorithms for PCB images enhancement.....114
4.2.1. Flood fill algorithm.....117
4.2.2. Multilevel segmentation of PCB images.....119
4.2.3. PCB images enhancement by К-mean clustering.....122
4.3. PCB model for start points detection.....123
4.3.1. PCB image model.....127
4.3.2. PCB image contacts detection.....129
4.3.3. Assigning PCB contacts to chains.....136
4.4. Short and open PCB defects detection.....136
4.5. Defects detection in traces.....139
4.6. Defects detection by subtraction and clustering.....142
4.7. Shift, connectivity and trace defects detection by comparison of mask images.....150
4.8. Conclusion.....157
Chapter 5. Extraction and analysis efface features.....158
5.1. Parametric statistical features for one level partitioning.....158
5.2. Face images multilevel segmentation and classification by clustering algorithm.....168
5.3. Face Images and its fragments classification by clustering.....173
5.4. Features effaces by distributed cumulative histogram.....178
5.5. Face profile features extraction.....185
5.6. Conclusions.....195
Chapter 6. Detection of defects in material surfaces.....196
6.1. Partitioning algorithms for defects detection.....196
6.2. Defect intensity measurement by distributed cumulative histogram and clustering.....203
6.3. Defects measurement by intensity fragments clustering.....211
6.3.1. Image transformation and relative intensity clustering.....215
6.3.2. Defects measurement by clustering of distributed cumulative histogram.....216
6.4. Image approximation for defects detection.....222
6.5 Defects detection m textured images.....229
6.5. Defects detection by clustering and rotating image.....239
6.6. Conclusion.....246
Chapter 7. Cloudiness analysis by statistical features and clustering.....248
7.1. Two simple methods for cloudiness analysis.....248
7.2. Deleting influence of neighboring territories.....252
7.3. Classification of clouds by statistical characteristics of images.....259
7.4. Analysis of cloudiness by color concentration features.....261
7.5. Centers of mathematical expectation of pixel coordinates.....268
7.6. Classification of cloudiness by features clustering.....274
7.7. Three-stages clustering algorithm for clouds analysis.....280
7.8. Analysis of moving cloud direction and velocity.....287
7.9. Conclusion.....299
References.....300
Supplement.....304

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