by Peng-Yeng Yin
Publisher: IN-TECH 2008
Number of pages: 626
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. The 27 chapters in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition.
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by Simon J.D. Prince - Cambridge University Press
This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use data to learn the relationships between the observed image data and the aspects that we wish to estimate.
by Pei-Gee Ho - InTech
The objective of the image segmentation is to simplify the representation of pictures into meaningful information by partitioning into image regions. Image segmentation is a technique to locate certain objects or boundaries within an image.
by Scott Krig - Springer
Provides an extensive survey of over 100 machine vision methods, with a detailed taxonomy for local, regional and global features. It provides background to develop intuition about why interest point detectors and feature descriptors actually work.
by Dilip K. Prasad - arXiv
We propose a new object detection/recognition method, which improves over the existing methods in every stage of the object detection/recognition process. In addition to the usual features, we propose to use geometric shapes as additional features.