A Bayesian approach to vectorization of object boundaries from digital images and to geometrical uncertainty assessment

2011 ◽  
Vol 28 (5) ◽  
pp. 448-466
Author(s):  
Francesco Finazzi
Keyword(s):  
Bayesian Approach ◽  
Digital Images ◽  
Uncertainty Assessment ◽  
Geometrical Uncertainty

Integrated treatment of model and parameter uncertainties through a Bayesian approach

2012 ◽  
Vol 227 (1) ◽  
pp. 41-54 ◽  
Author(s):  
Enrique López Droguett ◽  
Ali Mosleh
Keyword(s):  
Bayesian Approach ◽  
Model Uncertainty ◽  
Integrated Assessment ◽  
Model Averaging ◽  
Uncertainty Assessment ◽  
Integrated Treatment ◽  
Parameter Uncertainties ◽  
Bayesian Approaches ◽  
Uncertainty Factor ◽  
Special Cases

Bayesian and non-Bayesian approaches have been proposed for treating model uncertainty; in general, model and parameter uncertainties have been tackled as separate domains. This article discusses a Bayesian framework for an integrated assessment of model and parameter uncertainties. The approach accommodates cases involving multiple dependent models, and we also demonstrate that under certain conditions, the model uncertainty assessment approaches known as model averaging and uncertainty-factor are special cases of the proposed formulation. These features are also demonstrated by means of a few examples of interest in the risk and safety domain.

Reduction in size of digital images: does it lead to less detectability or loss of diagnostic information?

1998 ◽  
Vol 27 (2) ◽  
pp. 93-96 ◽  
Author(s):  
C H Versteeg ◽  
G C H Sanderink ◽  
S R Lobach ◽  
P F van der Stelt
Keyword(s):  
Digital Images ◽  
Diagnostic Information

Development of a system for craniofacial analysis from monitor-displayed digital images

1999 ◽  
Vol 28 (2) ◽  
pp. 123-126 ◽  
Author(s):  
E Gotfredsen ◽  
J Kragskov ◽  
A Wenzel
Keyword(s):  
Digital Images

Authentication of Digital Image using Exif Metadata and Decoding Properties

2018 ◽  
pp. 335-341 ◽  
Author(s):  
D. P. Gangwar ◽  
Anju Pathania
Keyword(s):  
Digital Image ◽  
Digital Images ◽  
Software Tools ◽  
Robust Analysis

This work presents a robust analysis of digital images to detect the modifications/ morphing/ editing signs by using the image’s exif metadata, thumbnail, camera traces, image markers, Huffman codec and Markers, Compression signatures etc. properties. The details of the whole methodology and findings are described in the present work. The main advantage of the methodology is that the whole analysis has been done by using software/tools which are easily available in open sources.

Sign in / Sign up

Export Citation Format

Share Document