Computer Vision Metrics: Survey, Taxonomy, and Analysis
by Scott Krig
Publisher: Springer 2014
Number of pages: 498
Provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, how they are designed, with observations about tuning the methods for achieving robustness and invariance targets for specific applications.
Home page url
Download or read it online for free here:
by Peng-Yeng Yin - IN-TECH
The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms.
by Julio Ponce, Adem Karahoca - IN-TECH
Nearest feature classification for face recognition, subspace methods, a multi-stage classifier for face recognition undertaken by coarse-to-fine strategy, PCA-ANN face recognition system based on photometric normalization techniques, etc.
by R. Jain, R. Kasturi, B. G. Schunck - McGraw-Hill
The book is intended to provide a balanced introduction to machine vision. Basic concepts are introduced with only essential mathematical elements. The details to allow implementation and use of vision algorithm in practical application are provided.
by Rong-Fong Fung - InTech
This is a book about how to employ the vision theory in the market conditions for students or researchers who want to realize the technique of machine vision. The book consists of 10 chapters on different fields about vision applications.