Filtering, Segmentation and Depth / Edition 1

Filtering, Segmentation and Depth / Edition 1

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by Mark Nitzberg, David Mumford, Takahiro Shiota
     
 

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

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Overview

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.

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Product Details

ISBN-13:
9783540564843
Publisher:
Springer Berlin Heidelberg
Publication date:
05/07/1993
Series:
Lecture Notes in Computer Science Series, #662
Edition description:
1993
Pages:
152
Product dimensions:
9.21(w) x 6.14(h) x 0.34(d)

Table of Contents

Overview.- Filtering for occlusion detection.- Finding contours and junctions.- Continuations.- Finding the 2.1D sketch.- Conclusion.

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