Recovering and characterizing image features using an efficient model based approach

TLDR: The development of an efficient model-based approach to detect and characterize precisely important features such as edges, corners and vertices is discussed and some efficient models associated to each of these features directly from the image by searching the parameters of the model that best approximate the observed grey level image intensities.

Abstract: The development of an efficient model-based approach to detect and characterize precisely important features such as edges, corners and vertices is discussed. The key is to propose some efficient models associated to each of these features directly from the image by searching the parameters of the model that best approximate the observed grey level image intensities. Due to the large amount of time required by a first approach that assumes the blur of the imaging acquisition system to be describable by a 2-D Gaussian filter, different solutions that drastically reduce this computational time are considered and developed. The problem of the initialization phase in the minimization process is considered, and an original and efficient solution is proposed. A large number of experiments involving real images are conducted in order to test and compare the reliability, the robustness, and the efficiency of the proposed approaches. >

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Recovering and Characterizing Image Features Using An
Ecient Model Based Approach
Thierry Blaszka, Rachid Deriche
To cite this version:
Thierry Blaszka, Rachid Deriche. Recovering and Characterizing Image Features Using An Ecient
Model Based Approach. RR-2422, INRIA. 1994. �inria-00074253�

ISSN 0249-6399
apport 

de recherche
1994
INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET EN AUTOMATIQUE
Recovering and Characterizing Image Features
Using An Efficient Model Based Approach
Thierry Blaszka, Rachid Deriche
N˚ 2422
Novembre 1994
PROGRAMME 4
Robotique,
image
et vision

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