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Michela Lecca

Permanent researcher
  • Phone: 0461314536
  • FBK Povo
Short bio

Michela received her Master Degree in Mathematics from the University of Trento, Italy. She is currently researcher at the Research Unit Technologies of Vision of Fondazione Bruno Kessler of Trento, Italy. Her research interests include automatic object recognition, image retrieval, semantic image labeling, color constancy, color correction, and low-level image processing. From 2014, Michela collaborates with the research Unit IRIS (FBK-CMM) on hardware-oriented computer vision topics.

Michela took part to the program committee of many editions of Applied Computing Machine Symposia, and carries on a reviewing activity for several international conferences. She is a member of the International Association for Pattern Recognition -  Associazione Italiana per la ricerca in Computer Vision, Pattern recognition e machine Learning IAPR - CVPL (ex GIRPR) and of the Gruppo Italiano del Colore - Associazione Italiana Colore (GdC-AIC).

FBK Learnintg & Development Courses:

Michela participated to the following FBK training activities:

  • Infographics & data visualization (17/04/2018)
  • Comunicare FBK (10/11/2017)
  • Comunicare la Scienza / Media Writing (14/09/2017)


  • August 2018: Michela is a Guest Editor of the Special Issue on J. of Imaging Image Enhancement, Modeling and Visualization. The call for paper is published on the journal website, deadline on August 12, 2018 (EXTENDED!)
  • February 2018: Michela was a co-organizer of the Workshop "Mathematics for Computer Vision" (MCV 2018), hosted by FBK - ICT on February 15-16, 2018.
  • September 2017: Michela, along with her colleagues at IRIS, participated at the Notte dei Ricercatori and presented some outcomes of the EU Project FORENSOR (Visione Intelligente a Basso Consumo / Ecco la telecamera anti-crimine!).
  • March 2017: Michela presented a Tutorial on Retinex theory at the 6th Computational Color Imaging Workshop (Milano, Italy.
  • Since December 2016, Michela is a co-author of the Column Communcations and Comments of the Journal "Cultura e Scienza del Colore - Color Culture and Science of the Gruppo del Colore - Associazione Italiana Colore.
  • 2015-2016: Michela led a Research in Pairs with the University of Trento, Department of Mathematics, and the University of Milano, Department of Computer Science. "Research in Pairs" is a program of FBK-CIRM, that promotes the collaboration among different research centers and/or university on topics mainly related to Mathematics. The research in pairs involving Michela focuses on the development of variational models for estimating the human color sensation. The main findings of this research have been published on JOSA A  and on IEEE TIP
Research interests
object recognition semantic image labeling color constancy color correction hardware oriented image processing
  1. Michela Lecca,
    An Attention Module for Object Detection in Cluttered Images,
    , pp. 68 -
  2. Michela Lecca; Stefano Messelodi,
    Illuminant Change Estimation via Minimization of Color Histogram Divergence,
    Computational Color Imaging Workshop,
    n. LNCS 5646,
    , pp. 41-
    , (Computational Color Imaging Workshop,
    Saint-Etienne, France,
    03/26/2009 - 03/27/2009)
  3. Paola Lecca; Lorenzo Demattè; Michela Lecca; Corrado Priami,
    Stochastic modelling of diffusion systems. Video image simulation of tubulin diffusion in cytoplasm: a case study,
    II ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing,
    , (II ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing,
    Porto, Portugal,
    14/10/2009 - 16/10/2009)
  4. Michela Lecca,
    The object classifier OC-COMPASS,
    This paper presents the nearest-neighbor object classifier OC-COMPASS, that recognizes rescaled, rotated, translated, relighted and partially occluded versions of the objects stored in one or more databases. This tool has been developed for browsing web catalogs by similarity and has been successfully integrated in a system for the automatic object recognition within color images.,
  5. Paola Lecca; Michela Lecca,
    A model of the Ca2+ and Na+ waves kinetics in astrocytes and its relevance to functional brain imaging,
    5th European Congress on Computational Methods in Applied Sciences and Engineering ECCOMAS,
    , pp. 2296-
    , (5th European Congress on Computational Methods in Applied Sciences and Engineering ECCOMAS,
    Venice, Italy,
    30/06/2008 - 04/07/2008)
  6. Paola Lecca; Michela Lecca,
    Modeling the molecular bases of glucose metabolism in astrocytes,
    XIX Congresso Nazionale Societa` Italiana di Biofisica Pura e Applicata - SIBPA 2008,
    , pp. 76-
    , (XIX Congresso Nazionale Societa` Italiana di Biofisica Pura e Applicata - SIBPA 2008,
    Rome, Italy,
    17/09/2008 - 20/09/2008)
  7. Michela Lecca; Stefano Messelodi,
    Estimating Illuminant Changes in Color Images by Color Histogram Comparison,
    The colors of a scene are strongly dependent on the light source. For this reason, the systems for image retrieval or object recognition based on the analysis of descriptors related to the colors, cannot work well when illuminant changes occur. This work proposes a novel method for estimating the changes of illuminants occurring between the images of a same scene captured under different photometric conditions. The illuminant variations are represented by the von Kries diagonal model and their estimate is performed by minimizing a dissimilarity measure between the color histograms of the images under examination. A technique for illuminant invariant image and object identification based on the estimates of the light changes is also presented, along with a comparison with other approaches.,
  8. Michela Lecca,
    Object Localization by Topological Coverages,
    Object recognition is a hard problem, especially when no a priori information about the presence and the positions of the objects to be searched are available. Here we present a new method for determining the image regions more likely occupied by each database object. The proposed technique is completely automatic and it can be used as pre-processing step in many object detection algorithms for reducing the space in which to search the objects in the image and therefore the computational costs.,
  9. Michela Lecca; Stefano Messelodi,
    Estimating Illuminant Changes by Piecewise Inversion of Cumulative Color Histograms,
    We present a new linear algorithm for the computation of the illuminant change occurring between two color images. We approximate the light variations by the von Kries diagonal transform, whose coefficients we estimate by minimizing a dissimilarity measure between the piecewise inversions of the cumulative color histograms of the considered images. We provide an analysis about the accuracy of our estimate and we explain how to use it for illuminant invariant image retrieval.,
  10. Michela Lecca; Stefano Messelodi,
    18th British Machine Vision Conference,
    , pp. 112-
    , (18th British Machine Vision Conference,
    Coventry, United Kingdom,
    10/09/2007 - 13/09/2007)