Feature Extraction and Image Processing for Computer Vision
Format:
Paperback
En stock
1.67 kg
Sí
Nuevo
Amazon
USA
- Feature Extraction and Image Processing for Computer Vision, Fifth Edition is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated, providing a link between theory and implementation. Essential background theory is carefully explained. This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation.Concentrates on feature extraction with working implementation and worked through mathematical derivations and algorithmic methodsProvides a thorough overview of available feature extraction methods, including essential background theory, shape methods, texture and deep learningIncludes up-to-date coverage of interest point detection, feature extraction and description, and image representation (including frequency domain and color)Includes a good balance between providing a mathematical background and practical implementation
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Focuses on feature extraction with practical implementation and detailed mathematical derivations and algorithmic methods Offers comprehensive coverage of available feature extraction methods, including foundational theory, shape analysis, texture, and deep learning techniques Covers recent developments in interest point detection, feature extraction and description, and image representation (including frequency domain and color) Strikes a good balance between providing mathematical theory and practical implementation