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Stefano Messelodi

Head of Unit
  • Phone: 0461314509
  • FBK Povo
Short bio

Stefano Messelodi was born in Arco (Italy) in 1961. He graduated in computer science from the University of Milan (Italy).  Since 1986 he is working in FBK (ITC-irst), Trento, Italy, where he coordinated the Technologies of Vision research unit till 2012. His research interests include text localization in scene, semantic image labelling and dynamic scene understanding. He served as a reviewer for several journals and conferences. He is a member of IEEE Society and International Association for Pattern Recognition.
He currently coordinates the research unit TeV.

Research interests
people re-identification text localization in scene document image analysis traffic analysis
Publications
  1. Bruno Caprile; T. Coianiz; Fausto Giunchiglia; Gianni Lazzari; Stefano Messelodi; G. Musso,
    Rapporto tecnico sullo studio di fattibilità per CIRCUIT LINE,
    1996
  2. Bruno Caprile; T. Coianiz; Gianni Lazzari; Stefano Messelodi,
    Rapporto tecnico sullo studio di fattibilità per CIRCUIT LINE Allineamento tra PCB e adattatore: acquisizione e misura,
    1996
  3. Bruno Caprile; T. Coianiz; Gianni Lazzari; Stefano Messelodi,
    Rapporto tecnico sullo studio di fattibilità per CIRCUIT LINE Allineamento tra PCB e adattatore: acquisizione e misura (seconda versione),
    1996
  4. Bruno Caprile; T. Coianiz; Gianni Lazzari; Stefano Messelodi,
    Note sulla localizzazione ottica dei fori di riferimento di un circuito stampato,
    1996
  5. Stefano Messelodi; Carla Maria Modena,
    VCB: Video Clip Browser and more - User's Guide for Version 1.1,
    1996
  6. F. Fignoni; Stefano Messelodi; Carla Maria Modena,
    Review of the State of the Art in Optical Character Recognition. Part 1: Machine Printed Documents,
    Machine understanding of documents has become a fundamental element in applications dealing with large quantities of text and images. The main purpose of the present report is to make light on the crowded world of document reading products. We intend to describe the main features and drawback of these systems and to highlight some criteria for their correct evaluation. Finally, we review briefly the research fields currently investigated in order to improve the performances of the current document recognition systems. This review covers only OCR systems specifically designed for reading documents containing text with little or no a priori information about the layout of the page, usually called page readers. This task is different from the one of reading pre-printed forms, for instance payment forms, where knowledge about the specific layout and format is complete. Also, dealing with forms usually means higher thorughput, which implies special purpose hardware: our review covers software products only. This review is based on the technology assessment of OCR products that takes place, annually since 1992, at the Information Science Institute (ISRI) at the University of Nevada, Las Vegas,
    1996
  7. F. Fignoni; Stefano Messelodi; Carla Maria Modena,
    Rassegna su OCR dattiloscritto: Implicazioni sul progetto Grandi Archivi Multimediali,
    1996
  8. F. Fignoni; Stefano Messelodi; Carla Maria Modena,
    Review of the State of the Art in Optical Character Recognition. Part 2: Hand Printed Documents,
    The automatic recognition of hand written text is an important practical problem with a great variety of potential applications: fax reading, form reading, help to blind people, signature verification, check reading, code recognition, address reading, document database population, and many more. Therefore, the interest of academic groups and commercial associations in hand written recognition is high. In this state of the art review, we address the field of the off-line recognition of unconstrained hand printed characters. We illustrate the results of two comparative tests of ICR systems conducted by NIST: the first deals with the recognition of isolated hand printed characters and the second with the reading of hand printed words from U.S. census forms. Starting from these results and from our experience, we focus our attention on the available commercial products we consider the most reliable. Finally, we present recent trends of the academic research in this area of machine vision, aiming at identifying the most challenging fields for future research,
    1996
  9. Roberto Brunelli; Stefano Messelodi,
    Robust Estimation of Correlation with Applications to Computer Vision,
    in «PATTERN RECOGNITION»,
    vol. 28,
    n. 6,
    1995
    , pp. 833 -
    841
  10. Alessandro Leonardi; Stefano Messelodi; Luigi Stringa,
    Book Recognition as an Example of Flat and Structured Objects Classification,
    in «CYBERNETICS AND SYSTEMS»,
    vol. 26,
    n. 6,
    1995
    , pp. 621 -
    645

Pages