Logo

Machine Vision by R. Jain, R. Kasturi, B. G. Schunck

Large book cover: Machine Vision

Machine Vision
by

Publisher: McGraw-Hill
ISBN/ASIN: 0070320187
ISBN-13: 9780070320185
Number of pages: 549

Description:
This text 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, and engineering aspects of techniques are emphasized. This text intentionally omits theories of machine vision that do not have sufficient practical applications at the time.

Home page url

Download or read it online for free here:
Download link
(multiple PDF files)

Similar books

Book cover: Vision SystemsVision Systems
by - Cardiff School of Computer Science
From the table of contents: Image Acquisition: 2D Image Input, 3D imaging; Image processing: Fourier Methods, Smoothing Noise; Edge Detection; Edge Linking; Segmentation; Line Labelling; Relaxation Labelling; Optical Flow; Object Recognition.
(8338 views)
Book cover: Notes on Elementary Spectral Graph TheoryNotes on Elementary Spectral Graph Theory
by - arXiv
These are notes on the method of normalized graph cuts and its applications to graph clustering. I provide a thorough treatment of this deeply original method, including complete proofs. The main thrust of this paper is the method of normalized cuts.
(4528 views)
Book cover: Anisotropic Diffusion in Image ProcessingAnisotropic Diffusion in Image Processing
by - Teubner
Many recent techniques for digital image enhancement and multiscale image representations are based on nonlinear PDEs. This book gives an introduction to the main ideas behind these methods, and it describes in a systematic way their foundations.
(8981 views)
Book cover: Pattern RecognitionPattern Recognition
by - 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.
(9361 views)