- Email: [email protected]
Variable pyramid structures for image semgentation
COMPUTERVISION, GRAPHICS,AND IMAGE PROCESSING49,125-126
(1990)
Abstracts of Papers Accepted for Publication PAPERS S. BARONTI,A. CASINI, AND F. LOCI. Istituto di Pyramid Structures for Image Segmentation. Ricerca sulle Onde Elettromagnetiche, Consiglio Nazionale delle Ricerche, IROE-CNR, via Panciatichi 64, 50127, Florence, Italy. L. FAVARO AND V. ROBERTO. Universita degli Studi di Udine, Dipartimento di Matematica, e Informatica, via Zanon 6, 33100 Udine, Italy. Received December 16, 1987; revised April 12, 1989.
Variabk
Linked pyramid structures have proved to be a useful tool in digital image processing for many applications because of their ability to face problems at different levels of detail. Some variations suggested by usage to existent pyramid algorithms have been investigated for the segmentation of compact objects in noisy IR images. In particular, the efficacy of increasing the span at the very last iterations in order to correct the link deficiency of the boundary nodes is reported. We also report about a method which individuates segment roots at any level in the pyramid and merges the segments under the constraint of the maximum number of regions to be distinguished. The method is applied to IR image segmentation and comparative results are given. The Estimation a Parametric
of Geometry Model.
and Motion
of a Surface
from
Image
Sequences
by Means
of Linearization
of
M. J. KORSTENAND Z. HOUKFS. Department Vision, Control Systems, and Computer Engineering Laboratory, Faculty of Electrical Engineering, University of Twente, P.O. Box 217, 7500AE Enschede, The Netherlands. Received August 13,1987; accepted May 5, 1989.
A method is given to estimate the geometry and motion of a moving body surface from image sequences. To this aim a parametric model of the surface is used, in order to reformulate the problem to one of parameter estimation. After linearization of the model, standard linear estimation methods can be used to estimate the parameters. The main contribution of this paper is that a method is provided to perform the linearization without specifying the model. Therefore structure from motion estimation and nonrigid body motion estimation can be performed regardless of the model. Afgeb~ An Overview. G. X. RITTER, J. N. WILSON, AND J. L. DAVIDSON. Center for Computer Vision Research, Department of Computer and Information Sciences, University of Florida, Gainesville, Florida 32611. Received July 29, 1988; revised April 17, 1989.
Image
This paper is the first in a sequence of papers describing an algebraic structure for image processing that has become known as the AFATL Stundmd Image Algebra This algebra provides a common mathematical environment for image processing algorithm development and methodologies for algorithm optimization, comparison, and performance evaluation. In addition, the image algebra provides a powerful algebraic language for image processing which, if properly embedded into a high level programming language, will greatly increase a programmer’s productivity as programming tasks are greatly simplified due to replacement of large blocks of code by short algebraic statements. The purpose of this paper is to familiarize the reader with the basic concepts of the algebra and to provide a general overview of its methodology.
NOTES Drawing Processing and Vectorization System VLIAY NAGA~AMY AND NOSH~R A. LANGRANA. Department of Mechanical & Aerospace Engineering, Rutgers-The State University of New Jersey, P.O. Box 909, Piscataway, New Jersey 08855. Received October 27,1987; revised April 12, 1989. 125 0734-189X/90 $3.00 Copyright0 1990 by Academic Press,Inc.
Engineering
All rights of reproduction
in any form reserved.
(1990)
Abstracts of Papers Accepted for Publication PAPERS S. BARONTI,A. CASINI, AND F. LOCI. Istituto di Pyramid Structures for Image Segmentation. Ricerca sulle Onde Elettromagnetiche, Consiglio Nazionale delle Ricerche, IROE-CNR, via Panciatichi 64, 50127, Florence, Italy. L. FAVARO AND V. ROBERTO. Universita degli Studi di Udine, Dipartimento di Matematica, e Informatica, via Zanon 6, 33100 Udine, Italy. Received December 16, 1987; revised April 12, 1989.
Variabk
Linked pyramid structures have proved to be a useful tool in digital image processing for many applications because of their ability to face problems at different levels of detail. Some variations suggested by usage to existent pyramid algorithms have been investigated for the segmentation of compact objects in noisy IR images. In particular, the efficacy of increasing the span at the very last iterations in order to correct the link deficiency of the boundary nodes is reported. We also report about a method which individuates segment roots at any level in the pyramid and merges the segments under the constraint of the maximum number of regions to be distinguished. The method is applied to IR image segmentation and comparative results are given. The Estimation a Parametric
of Geometry Model.
and Motion
of a Surface
from
Image
Sequences
by Means
of Linearization
of
M. J. KORSTENAND Z. HOUKFS. Department Vision, Control Systems, and Computer Engineering Laboratory, Faculty of Electrical Engineering, University of Twente, P.O. Box 217, 7500AE Enschede, The Netherlands. Received August 13,1987; accepted May 5, 1989.
A method is given to estimate the geometry and motion of a moving body surface from image sequences. To this aim a parametric model of the surface is used, in order to reformulate the problem to one of parameter estimation. After linearization of the model, standard linear estimation methods can be used to estimate the parameters. The main contribution of this paper is that a method is provided to perform the linearization without specifying the model. Therefore structure from motion estimation and nonrigid body motion estimation can be performed regardless of the model. Afgeb~ An Overview. G. X. RITTER, J. N. WILSON, AND J. L. DAVIDSON. Center for Computer Vision Research, Department of Computer and Information Sciences, University of Florida, Gainesville, Florida 32611. Received July 29, 1988; revised April 17, 1989.
Image
This paper is the first in a sequence of papers describing an algebraic structure for image processing that has become known as the AFATL Stundmd Image Algebra This algebra provides a common mathematical environment for image processing algorithm development and methodologies for algorithm optimization, comparison, and performance evaluation. In addition, the image algebra provides a powerful algebraic language for image processing which, if properly embedded into a high level programming language, will greatly increase a programmer’s productivity as programming tasks are greatly simplified due to replacement of large blocks of code by short algebraic statements. The purpose of this paper is to familiarize the reader with the basic concepts of the algebra and to provide a general overview of its methodology.
NOTES Drawing Processing and Vectorization System VLIAY NAGA~AMY AND NOSH~R A. LANGRANA. Department of Mechanical & Aerospace Engineering, Rutgers-The State University of New Jersey, P.O. Box 909, Piscataway, New Jersey 08855. Received October 27,1987; revised April 12, 1989. 125 0734-189X/90 $3.00 Copyright0 1990 by Academic Press,Inc.
Engineering
All rights of reproduction
in any form reserved.