05606nam 22007093u 450 991046530750332120210114232904.01-118-84873-X(CKB)2560000000147408(EBL)1659273(SSID)ssj0001212511(PQKBManifestationID)11788048(PQKBTitleCode)TC0001212511(PQKBWorkID)11210777(PQKB)11568791(CaSebORM)9781118848739(MiAaPQ)EBC1659273(EXLCZ)99256000000014740820140407d2014|||| u|| |engur|n|---|||||txtccrA Practical Introduction to Computer Vision with OpenCV[electronic resource]1st editionHoboken Wiley20141 online resource (235 p.)Description based upon print version of record.1-118-84845-4 Includes bibliographical references and index.A Practical Introduction to Computer Vision with OpenCV; Contents; Preface; 1 Introduction; 1.1 A Difficult Problem; 1.2 The Human Vision System; 1.3 Practical Applications of Computer Vision; 1.4 The Future of Computer Vision; 1.5 Material in This Textbook; 1.6 Going Further with Computer Vision; 2 Images; 2.1 Cameras; 2.1.1 The Simple Pinhole Camera Model; 2.2 Images; 2.2.1 Sampling; 2.2.2 Quantisation; 2.3 Colour Images; 2.3.1 Red-Green-Blue (RGB) Images; 2.3.2 Cyan-Magenta-Yellow (CMY) Images; 2.3.3 YUV Images; 2.3.4 Hue Luminance Saturation (HLS) Images; 2.3.5 Other Colour Spaces2.3.6 Some Colour Applications2.4 Noise; 2.4.1 Types of Noise; 2.4.2 Noise Models; 2.4.3 Noise Generation; 2.4.4 Noise Evaluation; 2.5 Smoothing; 2.5.1 Image Averaging; 2.5.2 Local Averaging and Gaussian Smoothing; 2.5.3 Rotating Mask; 2.5.4 Median Filter; 3 Histograms; 3.1 1D Histograms; 3.1.1 Histogram Smoothing; 3.1.2 Colour Histograms; 3.2 3D Histograms; 3.3 Histogram/Image Equalisation; 3.4 Histogram Comparison; 3.5 Back-projection; 3.6 k-means Clustering; 4 Binary Vision; 4.1 Thresholding; 4.1.1 Thresholding Problems; 4.2 Threshold Detection Methods; 4.2.1 Bimodal Histogram Analysis4.2.2 Optimal Thresholding4.2.3 Otsu Thresholding; 4.3 Variations on Thresholding; 4.3.1 Adaptive Thresholding; 4.3.2 Band Thresholding; 4.3.3 Semi-thresholding; 4.3.4 Multispectral Thresholding; 4.4 Mathematical Morphology; 4.4.1 Dilation; 4.4.2 Erosion; 4.4.3 Opening and Closing; 4.4.4 Grey-scale and Colour Morphology; 4.5 Connectivity; 4.5.1 Connectedness: Paradoxes and Solutions; 4.5.2 Connected Components Analysis; 5 Geometric Transformations; 5.1 Problem Specification and Algorithm; 5.2 Affine Transformations; 5.2.1 Known Affine Transformations; 5.2.2 Unknown Affine Transformations5.3 Perspective Transformations5.4 Specification of More Complex Transformations; 5.5 Interpolation; 5.5.1 Nearest Neighbour Interpolation; 5.5.2 Bilinear Interpolation; 5.5.3 Bi-Cubic Interpolation; 5.6 Modelling and Removing Distortion from Cameras; 5.6.1 Camera Distortions; 5.6.2 Camera Calibration and Removing Distortion; 6 Edges; 6.1 Edge Detection; 6.1.1 First Derivative Edge Detectors; 6.1.2 Second Derivative Edge Detectors; 6.1.3 Multispectral Edge Detection; 6.1.4 Image Sharpening; 6.2 Contour Segmentation; 6.2.1 Basic Representations of Edge Data; 6.2.2 Border Detection6.2.3 Extracting Line Segment Representations of Edge Contours6.3 Hough Transform; 6.3.1 Hough for Lines; 6.3.2 Hough for Circles; 6.3.3 Generalised Hough; 7 Features; 7.1 Moravec Corner Detection; 7.2 Harris Corner Detection; 7.3 FAST Corner Detection; 7.4 SIFT; 7.4.1 Scale Space Extrema Detection; 7.4.2 Accurate Keypoint Location; 7.4.3 Keypoint Orientation Assignment; 7.4.4 Keypoint Descriptor; 7.4.5 Matching Keypoints; 7.4.6 Recognition; 7.5 Other Detectors; 7.5.1 Minimum Eigenvalues; 7.5.2 SURF; 8 Recognition; 8.1 Template Matching; 8.1.1 Applications; 8.1.2 Template Matching Algorithm8.1.3 Matching MetricsExplains the theory behind basic computer vision and provides a bridge from the theory to practical implementation using the industry standard OpenCV libraries Computer Vision is a rapidly expanding area and it is becoming progressively easier for developers to make use of this field due to the ready availability of high quality libraries (such as OpenCV 2). This text is intended to facilitate the practical use of computer vision with the goal being to bridge the gap between the theory and the practical implementation of computer vision. The book will explain how to use the reComputer vision -- Computer programsComputer visionComputer visionComputer programsComputer visionEngineering & Applied SciencesHILCCApplied PhysicsHILCCElectronic books.Computer vision -- Computer programs.Computer vision.Computer visionComputer programsComputer visionEngineering & Applied SciencesApplied Physics006.3/7006.37Dawson-Howe Kenneth921570Dawson-Howe KennethAU-PeELAU-PeELAU-PeELBOOK9910465307503321A Practical Introduction to Computer Vision with OpenCV2067270UNINA