Machine Vision Inspection Systems, Image Processing, Concepts, Methodologies, and Applications

Index

• Abnormality, 184
• Aerial dataset, 5
• Antiphishing, 221
• Artificial intelligence, 119, 146
• Attribute data, 4
• Australia, 126–127
• Avocado,
  • dip, 151–160

• Benchmark, 183, 193, 195–196
• Bilateral filtering, 9
• Bivariate frequency histogram, 154, 158–159
• Blindness, 183–184
• Blood vessel, 192
• Bridge, 126, 142, 166, 167, 175, 176, 178
• Browser, 218, 225
• Built-up area, 12–14, 19, 21, 23

• Chain codes, 91, 92, 93
• Character recognition, 201
• Characteristic, 183
• Classification, 1–3, 6–9, 12, 13, 16–21, 25–28, 31–36, 218, 221
• Clinical, 183, 185, 188–191, 195–196
• Clustering, 14, 19
• Color,
  • analysis, 151–152, 154
  • distribution, 154–157
  • evolution, 155–156
  • invariance, 154, 159–160
  • plots, 156–157
  • space, 152–156, 159
• Computed PSNR value, 77, 78
• Computed PT, 78, 79
• Computed SNR value, 77, 78
• Computer vision, 151–152, 159–161
• Convolutional neural network, 203–2012
• Coverage, 1–3, 5–7, 21, 23, 30, 33, 34

• Damage, 119, 121, 122, 126, 142, 143, 147, 163, 164
• Data acquisition, 72
• Datamining, 221–223
• Decision tree, 26, 35
• Defects, 162, 163, 164, 166, 168, 170, 172, 177, 178
• Diabetes, 183–196
• Diabetic retinopathy, 183–186, 194
• Diagnose, 183, 185, 196
• Disaster, 164, 165, 168
• Disaster in Pakistan, 120, 122, 123
• Dynamic security skins, 220

• Edge detection, 72
• Edge enhancement, 9
• E-mail, 222, 223, 225
• Enhancement, 186, 190, 194, 195, 197

• Feature extraction, 73
• Felzenszwalb’s method, 22
• Floods, 119–146
• Food,
  • industry, 151
  • science, 159–162
• Fourier descriptors, 102, 103
• Foursquare data, 1, ...