Pattern RecognitionPeng-Yeng Yin For more than 40 years, pattern recognition approaches are continuingly improving and have been used in an increasing number of areas with great success. This book discloses recent advances and new ideas in approaches and applications for pattern recognition. The 30 chapters selected in this book cover the major topics in pattern recognition. These chapters propose state-of-the-art approaches and cutting-edge research results. I could not thank enough to the contributions of the authors. This book would not have been possible without their support. |
Contents
Background modelling with associated confidence | 15 |
New Trends in Motion Segmentation | 31 |
Volume Decomposition and Hierarchical Skeletonization | 47 |
Structure and Motion from Image Sequences based | 73 |
A Robust Iterative Multiframe SRR based on Hampel | 99 |
An Approach to Foreground Detection in Videos | 123 |
Application of the Wrapper Framework for Robust Image | 151 |
Projective Registration with Manifold Optimization | 175 |
Multidirectional Binary Pattern for Face Recognition | 267 |
Bayesian Video Face Detection with Applications | 281 |
3D Human Posture Estimation Using HOG Features | 295 |
Pattern Recognition in Medical Image Diagnosis | 319 |
A Cellular Automaton Framework for Image Processing on GPU | 353 |
FigureGround Discrimination and DistortionTolerant | 377 |
Segmenting the License Plate Region Using a Color Model | 401 |
Automatic Approaches to Plant Meristem States Revelation | 419 |
Learning Pattern Classification Tasks with Imbalanced Data Sets | 193 |
Image Kernel for Recognition | 209 |
BIVSEE A Biologically Inspired Vision System | 249 |
An Approach to Textile Recognition | 439 |
Approaches to Automatic Seabed Classification | 461 |
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Common terms and phrases
accuracy applications approach artificial neural network background model Bayesian binarization branching camera candidate regions classification cluster color combination components Computer Vision data set database defined detection distance emotion equation estimation evaluation exponential map extracted feature vector feedback filter frames framework function Gaussian histogram IEEE IEEE Transactions Image Processing implementation input image inrush current iterations L2 norm label layer learning license plate Lie group Machine Learning matrix measure method motion neighbourhood systems neural network neurons noise object obtained optical flow optimization output parameters password Pattern Recognition performance pixel plant problem proposed relevant retrieval robust samples scene seabed selected sequence shape shown in Fig signal skeleton ſº spam speaker recognition SRR algorithm statistical structure support vector machines support vectors SVDDM technique testing texture threshold training data transformation tree values voxels wavelet β β