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Filtering, Segmentation and Depth

  • Book
  • © 1993

Overview

Authors:
  1. Mark Nitzberg
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  2. David Mumford
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  3. Takahiro Shiota
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 662)

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Table of contents (6 chapters)

  1. Front Matter

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  2. Overview

    Pages 1-12

  3. Filtering for occlusion detection

    Pages 13-31

  4. Finding contours and junctions

    Pages 33-49

  5. Continuations

    Pages 51-71

  6. Finding the 2.1D sketch

    Pages 73-81

  7. Conclusion

    Pages 83-86

  8. Back Matter

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Keywords

About this book

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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