Multiscale method for feature preserving compression

Date

1998-01-01

Author

Tarı, Zehra Sibel

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

166
views

0
downloads

Requirements fora good shape representation lead to descriptors that are object centered and that have the notion of scale. These representations usually take the form of shape skeletons at multiple detail levels. Classical tool for skeleton extraction is the grassfire equation, in which the process is lossless and the equation can be run backwards in order to obtain shape boundary from the shape skeleton. Many complicated strategies have been devised to assign significance to skeletal points in order to arrive at the skeleton scale space; A recent alternative approach is to introduce regularization directly to the skeleton extraction process, by combining diffusion with grassfire. Very recently, techniques: similar in spirit, which combine nonlinear smoothing of the shape boundary with the grassfire, in order to extract an axis based description, are presented independently. When diffusion is introduced into the formulation, inverse equation is no longer stable. This is the issue we will be addressing in the context of the method presented by Tari and Shah far extraction of nested symmetries from arbitrary images in arbitrary dimension. The basic tool used in the method is a specific distance function which is the steady-state solution of an elliptic boundary value problem. We present an inverse equation and show how one may obtain the whole distance surface from a sparse representation, providing a means for determining the shape boundary from the shape skeleton. The presented technique can be used for feature-preserving compression.

Subject Keywords

Feature-preserving compression, Multiple scale shape skeletons

URI

https://hdl.handle.net/11511/57032

DOI

https://doi.org/10.1117/12.304612

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Multiple linear regression model with stochastic design variables İslam, Muhammed Qamarul (Informa UK Limited, 2010-01-01) In a simple multiple linear regression model, the design variables have traditionally been assumed to be non-stochastic. In numerous real-life situations, however, they are stochastic and non-normal. Estimators of parameters applicable to such situations are developed. It is shown that these estimators are efficient and robust. A real-life example is given.
Experimental design with short-tailed and long-tailed symmetric error distributions Yilmaz, Yıldız Elif; Akkaya, Ayşen; Department of Statistics (2004) One-way and two-way classification models in experimental design for both balanced and unbalanced cases are considered when the errors have Generalized Secant Hyperbolic distribution. Efficient and robust estimators for main and interaction effects are obtained by using the modified maximum likelihood estimation (MML) technique. The test statistics analogous to the normal-theory F statistics are defined to test main and interaction effects and a test statistic for testing linear contrasts is defined. It is ...
Comparison of regression techniques via Monte Carlo simulation Mutan, Oya Can; Ayhan, Hüseyin Öztaş; Department of Statistics (2004) The ordinary least squares (OLS) is one of the most widely used methods for modelling the functional relationship between variables. However, this estimation procedure counts on some assumptions and the violation of these assumptions may lead to nonrobust estimates. In this study, the simple linear regression model is investigated for conditions in which the distribution of the error terms is Generalised Logistic. Some robust and nonparametric methods such as modified maximum likelihood (MML), least absolut...
Landmarks inside the shape: Shape matching using image descriptors Guler, R. A.; Tarı, Zehra Sibel; ÜNAL, GÖZDE (2016-01-01) In the last few decades, significant advances in image matching are provided by rich local descriptors that are defined through physical measurements such as reflectance. As such measurements are not naturally available for silhouettes, existing arsenal of image matching tools cannot be utilized in shape matching. We propose that the recently presented SPEM representation can be used analogous to image intensities to detect local keypoints using invariant image salient point detectors. We devise a shape sim...
Shape models based on elliptic PDES, associated energies, and their applications in 2D and 3D Gençtav, Aslı; Tarı, Zehra Sibel; Can, Tolga; Department of Computer Engineering (2018) By using an elliptic PDE or its modifications, we develop implicit shape representations and demonstrate their two- and three-dimensional applications. In the first part of the thesis, we present a novel shape characterization field that provides a local measure of roundness at each shape point. The field is computed by comparing the solution of the elliptic PDE on the shape domain and the solution of the same PDE on the reference disk. We demonstrate its potential via illustrative applications including gl...

Citation Formats

Z. S. Tarı, “Multiscale method for feature preserving compression,” 1998, vol. 3304, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/57032.