Attributed tree data structure for representing the descriptions of object contours in images

Z. Ren; Walter Ameling; Peter F. Jensch

doi:10.1117/12.24110

1 September 1990 Attributed tree data structure for representing the descriptions of object contours in images

Z. Ren, Walter Ameling, Peter F. Jensch

Proceedings Volume 1360, Visual Communications and Image Processing '90: Fifth in a Series; (1990) https://doi.org/10.1117/12.24110
Event: Visual Communications and Image Processing '90, 1990, Lausanne, Switzerland

Abstract

Shape of medical objects, such as the human bones or skeletons, conveys information about the object’s anatomic structures and their pathological states. The sectional contours of the objects, which are observable through computer tomograms, carry descriptive clues for analyzing shapes. To build and represent the descriptions of contours, one should derive stable structural elements and their sensitive attributes from the contours. Sectional contours of the medical objects are highly curved and complex, therefore, they should be described in a higher order parameter space than just in a linear one. These considerations have guided us to examine the scale-space transformation, and to develop methods for expressing, describing, and extracting structures in the scale-space images of the contours. In this paper we introduce a tree-based data structure for representing descriptions of structures in the scale-space, and further demonstrate its applications to shape analysis.

Citation Download Citation

Z. Ren, Walter Ameling, and Peter F. Jensch "Attributed tree data structure for representing the descriptions of object contours in images", Proc. SPIE 1360, Visual Communications and Image Processing '90: Fifth in a Series, (1 September 1990); https://doi.org/10.1117/12.24110

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available