Filtering, Segmentation And Depth (lecture Notes In Computer Science)

"Computer vision seeks a process that starts with a noisy, ambiguous signal from a TV camera and ends with a high-level description of discrete objects located in 3-dimensional space and identified in a human classification. This book addresses the process at several levels. First to be treated are the low-level image-processing issues of noise removaland smoothing while preserving important lines and singularities in an image. At a slightly higher level, a robust contour tracing algorithm is described that produces a cartoon of the important lines in the image. Thirdis the high-level task of reconstructing the geometry of objects in the scene. The book has two aims: to give the computer vision community a new approach to early visual processing, in the form of image segmentation that incorporates occlusion at a low level, and to introduce real computer algorithms that do a better job than what most vision programmers use currently. The algorithms are: - a nonlinear filter that reduces noise and enhances edges, - an edge detector that also finds corners and produces smoothed contours rather than bitmaps, - an algorithm for filling gaps in contours."--PUBLISHER'S WEBSITE

computer Vision Seeks A Process That Starts With A Noisy,
ambiguous Signal From A Tv Camera And Ends With A High-level Description Of Discrete Objects Located In 3-dimensional Space And Identified In A Human Classification.
this Book Addresses The Process At Several Levels. First To Be Treated Are The Low-level Image-processing Issues Of Noise Removaland Smoothing While Preserving Important Lines And Singularities In An Image. At A Slightly Higher Level, A Robust Contour Tracing Algorithm Is Described That Produces A Cartoon Of The Important Lines In The Image. Thirdis The High-level Task Of Reconstructing The Geometry Of Objects In The Scene.
the Book Has Two Aims: To Give The Computer Vision Community A New Approach To Early Visual Processing, In The Form Of Image Segmentation That Incorporates Occlusion At A Low Level, And To Introduce Real Computer Algorithms That Do A Better Job Than What Most Vision Programmers Use Currently.
the Algorithms Are:
- A Nonlinear Filter That Reduces Noise And Enhances Edges,
- An Edge Detector That Also Finds Corners And Produces Smoothed Contours Rather Than Bitmaps,
- An Algorithm For Filling Gaps In Contours.

Overview....Pages 1-12 Filtering for occlusion detection....Pages 13-31 Finding contours and junctions....Pages 33-49 Continuations....Pages 51-71 Finding the 2.1D sketch....Pages 73-81 Conclusion....Pages 83-86