Digital image processing and analysis : human and computer vision applications with CVIPtools

著者

書誌事項

Digital image processing and analysis : human and computer vision applications with CVIPtools

Scott E Umbaugh

CRC Press, c2011

2nd ed

  • : hardback

大学図書館所蔵 件 / 全3件

この図書・雑誌をさがす

注記

Includes bibliographical references and index

内容説明・目次

内容説明

Whether for computer evaluation of otherworldly terrain or the latest high definition 3D blockbuster, digital image processing involves the acquisition, analysis, and processing of visual information by computer and requires a unique skill set that has yet to be defined a single text. Until now. Taking an applications-oriented, engineering approach, Digital Image Processing and Analysis provides the tools for developing and advancing computer and human vision applications and brings image processing and analysis together into a unified framework. Providing information and background in a logical, as-needed fashion, the author presents topics as they become necessary for understanding the practical imaging model under study. He offers a conceptual presentation of the material for a solid understanding of complex topics and discusses the theory and foundations of digital image processing and the algorithm development needed to advance the field. With liberal use of color through-out and more materials on the processing of color images than the previous edition, this book provides supplementary exercises, a new chapter on applications, and two major new tools that allow for batch processing, the analysis of imaging algorithms, and the overall research and development of imaging applications. It includes two new software tools, the Computer Vision and Image Processing Algorithm Test and Analysis Tool (CVIP-ATAT) and the CVIP Feature Extraction and Pattern Classification Tool (CVIP-FEPC). Divided into five major sections, this book provides the concepts and models required to analyze digital images and develop computer vision and human consumption applications as well as all the necessary information to use the CVIPtools environment for algorithm development, making it an ideal reference tool for this fast growing field.

目次

Section I Introduction to Digital Image Processing and Analysis Digital Image Processing and Analysis Overview Image Analysis and Computer Vision Image Processing and Human Vision Key Points Exercises References Further Reading Computer Imaging Systems Imaging Systems Overview Image Formation and Sensing CVIPtools Software Image Representation Key Points Exercises Supplementary Exercises References Further Reading Section II Digital Image Analysis and Computer Vision Introduction to Digital Image Analysis Introduction Preprocessing Binary Image Analysis Key Points Exercises Supplementary Exercises References Further Reading Segmentation and Edge/Line Detection Introduction and Overview Edge/Line Detection Segmentation Key Points Exercises Supplementary Exercises References Further Reading Discrete Transforms Introduction and Overview Fourier Transform Discrete Cosine Transform Discrete Walsh-Hadamard Transform Discrete Haar Transform Principal Components Transform Filtering Discrete Wavelet Transform Key Points Exercises Supplementary Exercises References Further Reading Feature Analysis and Pattern Classification Introduction and Overview Feature Extraction Feature Analysis Pattern Classification Key Points Exercises Supplementary Exercises References Further Reading Section III Digital Image Processing and Human Vision Digital Image Processing and Visual Perception Introduction and Overview Human Visual Perception Image Fidelity Criteria Key Points Exercises Supplementary Exercises References Further Reading Image Enhancement Introduction and Overview Gray-Scale Modification Image Sharpening Image Smoothing Key Points Exercises Supplementary Exercises References Further Reading Image Restoration and Reconstruction Introduction and Overview Noise Models Noise Removal Using Spatial Filters Degradation Function Frequency Domain Filters Geometric Transforms Image Reconstruction Key Points Exercises Supplementary Exercises References Further Reading Image Compression Introduction and Overview Lossless Compression Methods Lossy Compression Methods Key Points Exercises Supplementary Exercises References Further Reading Section IV Programming and Application Development with CVIPtools CVIPlab Introduction to CVIPlab Toolkits, Toolboxes, and Application Libraries Compiling and Linking CVIPlab Image Data and File Structures CVIP Projects Application Development Introduction and Overview CVIP Algorithm Test and Analysis Tool CVIP Feature Extraction and Pattern Classification Tool Skin Lesion Classification Using Relative Color Features Automatic Segmentation of Blood Vessels in Retinal Images Classification of Land Types from Satellite Images Using Quadratic Discriminant Analysis and Multilayer Perceptrons Watershed-Based Approach to Skin Lesion Border Segmentation Faint Line Defect Detection in Microdisplay (CCD) Elements Melanoma and Seborrheic Keratosis Differentiation Using Texture Features Compression of Color Skin Tumor Images with Vector Quantization References CVIPtools C (R) Function Libraries Introduction and Overview Arithmetic and Logic Library: ArithLogic.lib Band Image Library: Band.lib Color Image Library: Color.lib Compression Library: Compression.lib Conversion Library: Conversion.lib Display Library: Display.lib Feature Extraction Library: Feature.lib Geometry Library: Geometry.lib Histogram Library: Histogram.lib Image Library: Image.lib Data Mapping Library: Mapping.lib Morphological Library: Morphological.lib Noise Library: Noise.lib Segmentation Library: Segmentation.lib Spatial Filter Library: SpatialFilter.lib Transform Library: Transform.lib Transform Filter Library: TransformFilter.lib Section V Appendices CVIPtools CD Installing and Updating CVIPtools CVIPtools Software Organization CVIPtools C (R) Functions Common Object Module (COM) Functions: cviptools.dll CVIP Resources Index

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