Filtering, Segmentation and Depth [electronic resource] /

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.

Bibliographic Details

Main Authors:	Nitzberg, Mark. author., Mumford, David. author., Shiota, Takahiro. author., SpringerLink (Online service)
Format:	Texto biblioteca
Language:	eng
Published:	Berlin, Heidelberg : Springer Berlin Heidelberg, 1993
Subjects:	Computer science., Software engineering., Artificial intelligence., Image processing., Computer Science., Image Processing and Computer Vision., Artificial Intelligence (incl. Robotics)., Software Engineering/Programming and Operating Systems.,
Online Access:	http://dx.doi.org/10.1007/3-540-56484-5
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