Thomas Grenier

Archive for December, 2010

Digital Image Processing

by on Dec.09, 2010, under Image Processing, Teaching

Introduction to Digital Image Processing. These lectures are in english.

An example of exam (in french):

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Information Theory

by on Dec.09, 2010, under Signal Processing, Teaching

Basics of information theory : entropy, mutual information, Shannon theorems. All in french…

Lectures All (7.5MB)

  • 1-Entropie-Capacite
  • 2- Codage de Source
  • 3- Codage de Canal
  • 3a- Introduction au turbo codage

  • 3b- Problématique de compression d’image
  • 4- Cryptage

Some Exercices:

Examples of Exams

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C/C++

by on Dec.09, 2010, under Computer Science, Teaching

Langage C/C++ document for student (using QtCreator 2 as IDE/RAD) NoteCpp (1003kB)

Introduction to Algorithms and UML/C++ (short) [English]

Introduction to UML and OOP (C++) [French]

Practices C++ (without classes) [French]

Practices UML and C++ (with classes) [French]

Labs OOP  (with classes) [French]

  • TP POO_1 (178kB) TP1 Files (zip) (6kB)
  • TP POO_2 (87kB) TP2 Files (zip) (2kB)

  • 3D Robust Adaptive Region Growing

    by on Dec.08, 2010, under Region Growing, Research

    3D Robust Adaptive Region Growing for segmenting [18F]fluoride ion PET images

    We propose a new Robust Adaptive Region Growing method (RoAd RG) based on two local parameters: the local mean value of the intensity function and the local mean value of the norm of the intensity gradient. This approach enables a better spread of the region growing inside the region of interest while avoiding the merge of outlier pixels. We applied positively our method to 3D [18F]fluoride ion PET images for segmenting bone structures and showed its superiority compared to a non adaptive method. pdf (336kB)

    T. Grenier, C. Revol-Muller, N. Costes, M. Janier, G. Gimenez.

    Grenier, C. Revol-Muller, N. Costes, M. Janier, G. Gimenez.

    T. Grenier1, C. Revol-Muller1, N. Costes2, M. Janier1, 2, G. Gimenez1, 2

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    Multiparametric smoothing

    by on Dec.08, 2010, under Mean Shift, Research

    Multiparametric smoothing based on Mean shift procedure for ultrasound data segmentation

    Segmentation of ultrasound data is improved when using multi-parametric approach. In this paper we propose the use of Multi-Parametric Mean Shift procedure (MPMS). Two derived processes are described: MPMS smoothing which achieves a multi-parametric filtering in the spatial-range domain and MPMS segmentation which takes benefit of this filtering for segmenting the multidimensional data. MPMS segmentation is particularly attractive, since it achieves an unsupervised segmentation. These methods were positively tested on three sets of simulated ultrasonic data, representative of various scatterers densities and also various scattering conditions. pdf (690kB) Poster(733kB)

    Thomas Grenier, Chantal Revol-Muller, Franck Davignon, Olivier Basset, Gérard Gimenez.

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    Variable bandwidth mean shift

    by on Dec.08, 2010, under Mean Shift, Research

    ImageUS

    ImageUS

    Variable bandwidth Mean Shift for Smoothing ultrasonic images

    As the variance of the statistics of ultrasonic data in a homogeneous tissue may be rather large and the statistics of different tissues may be very similar, a new filtering approach is proposed to enhance the contrast in ultrasonic images. It is based on the Variable Bandwidth Mean Shift algorithm adapted to the specificities of ultrasonic data. A fully automatic adaptive bandwidth selection in both range and spatial domains is described. Our method was compared to a Variable Bandwidth Mean Shift algorithm based on an adaptive range scale selection and a fixed spatial scale parameter. The results show the superiority of our method. pdf (410kB) Poster (176kB)

    Thomas Grenier, Chantal Revol-Muller, Franck Davignon, Olivier Basset, Gérard Gimenez.

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    Digital Signal Processor

    by on Dec.08, 2010, under Computer Science, Teaching

    Digital_Signal_Processors_TG (5MB) DaVinci Introduction to Digital Signal Processor. Basics about architecture, fixed and floating point numbers, pipeline, MAC, buses… .

    A practice is also available TP-C54 (813kB) TP-C54.zip

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    Mean-shift filtering

    by on Dec.08, 2010, under Research

    Mean shift

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    Microcontroller PIC16

    by on Dec.08, 2010, under Computer Science, Teaching

    IF2_PIC16_Full (9MB) ImagePICThis lecture is a global presentation of microcontroller and a more specific understanding of PIC16 familly.

    Some exercices are also available here TDuC (6MB).

    3 practices are here (based on a dedicated kit)

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