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Edge and Depth from Focus

Authors
  • Asada, Naoki1
  • Fujiwara, Hisanaga2
  • Matsuyama, Takashi3
  • 1 Hiroshima City University, Department of Intelligent Systems, 63-4-1 Ozuka-Higashi, Asa-Minami, Hiroshima, 731-31, Japan. E-mail , Asa-Minami
  • 2 Industrial Research Center of Okayama, 5301 Haga, Okayama, 701-12, Japan E-mail , Okayama
  • 3 Kyoto University, Department of Electronics and Communication, Kyoto, 606-01, Japan. E-mail , Kyoto
Type
Published Article
Journal
International Journal of Computer Vision
Publisher
Springer-Verlag
Publication Date
Feb 01, 1998
Volume
26
Issue
2
Pages
153–163
Identifiers
DOI: 10.1023/A:1007996810301
Source
Springer Nature
Keywords
License
Yellow

Abstract

This paper proposes a novel method to obtain the reliable edge and depth information by integrating a set of multi-focus images, i.e., a sequence of images taken by systematically varying a camera parameter focus. In previous work on depth measurement using focusing or defocusing, the accuracy depends upon the size and location of local windows where the amount of blur is measured. In contrast, no windowing is needed in our method; the blur is evaluated from the intensity change along corresponding pixels in the multi-focus images. Such a blur analysis enables us not only to detect the edge points without using spatial differentiation but also to estimate the depth with high accuracy. In addition, the analysis result is stable because the proposed method involves integral computations such as summation and least-square model fitting. This paper first discusses the fundamental properties of multi-focus images based on a step edge model. Then, two algorithms are presented: edge detection using an accumulated defocus image which represents the spatial distribution of blur, and depth estimation using a spatio-focal image which represents the intensity distribution along focus axis. The experimental results demonstrate that the highly precise measurement has been achieved: 0.5 pixel position fluctuation in edge detection and 0.2% error at 2.4 m in depth estimation.

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