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图像数据挖掘基础:分析、特征、分类和检索-Fundamentals of Image Data Mining: Analysis, Features, Classification and Retri

上传于 2020-03-02 0次下载 5142次围观
标题(title):Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval
作者(author):Dengsheng Zhang
出版社(publisher):Springer International Publishing
大小(size):18 MB (18391354 bytes)

This reader-friendly textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical mathematical models and algorithms, utilizing data from real-world examples and experiments.
Topics and features: describes the essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms; reviews a varied range of state-of-the-art models, algorithms, and procedures for image mining; emphasizes how to deal with real image data for practical image mining; highlights how such features as color, texture, and shape can be mined or extracted from images for image representation; presents four powerful approaches for classifying image data, namely, Bayesian classification, Support Vector Machines, Neural Networks, and Decision Trees; discusses techniques for indexing, image ranking, and image presentation, along with image database visualization methods; provides self-test exercises with instructions or Matlab code, as well as review summaries at the end of each chapter.

This easy-to-follow work illuminates how concepts from fundamental and advanced mathematics can be applied to solve a broad range of image data mining problems encountered by students and researchers of computer science. Students of mathematics and other scientific disciplines will also benefit from the applications and solutions described in the text, together with the hands-on exercises that enable the reader to gain first-hand experience of computing.

Table of contents :
Front Matter ....Pages i-xxxi
Front Matter ....Pages 1-1
Fourier Transform (Dengsheng Zhang)....Pages 3-23
Windowed Fourier Transform (Dengsheng Zhang)....Pages 25-34
Wavelet Transform (Dengsheng Zhang)....Pages 35-44
Front Matter ....Pages 45-47
Color Feature Extraction (Dengsheng Zhang)....Pages 49-80
Texture Feature Extraction (Dengsheng Zhang)....Pages 81-111
Shape Representation (Dengsheng Zhang)....Pages 113-154
Front Matter ....Pages 155-159
Bayesian Classification (Dengsheng Zhang)....Pages 161-178
Support Vector Machine (Dengsheng Zhang)....Pages 179-205
Artificial Neural Network (Dengsheng Zhang)....Pages 207-242
Image Annotation with Decision Tree (Dengsheng Zhang)....Pages 243-259
Front Matter ....Pages 261-261
Image Indexing (Dengsheng Zhang)....Pages 263-270
Image Ranking (Dengsheng Zhang)....Pages 271-287
Image Presentation (Dengsheng Zhang)....Pages 289-304
Back Matter ....Pages 305-314
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图像数据挖掘基础:分析、特征、分类和检索-Fundamentals of Image Data Mining: Analysis, Features, Classification and Retri
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