IPI: Image Processing and Interpretation

Welcome to IPI, the Image Processing and Interpretation Research Group of the department TELIN of the Faculty of Faculty of Engineering and Architecture at Ghent University (Universiteit Gent).

Projects

IPI actively engages in collaborative research with other institutes and companies in the context of regional and European projects. We are currently active in the following collaborative projects:

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ACHIEVE

Researchers in ACHIEVE are designing highly integrated hardware-software components for the implementation of ultra-efficient embedded vision systems as the basis for innovative distributed vision applications

H2020-MSCA-ITN, 10/2017 – 9/2021

ANALYST PV

IPI researches integrated sensors and data analysis fault detection tools for photovoltaic plants

ICON project, 10/2019 – 9/2022

CHARAMBA

CHARAMBA aims to solve the problem of costly and labour-intensive sampling and chemical analysis of complex material/waste streams

EIT RawMaterials, 1/2020 - 12/2021

COSMO

In the COSMO project, researchers are designing, developing, and evaluating effective, personalized, and scalable AR and VR technologies for support and training in manufacturing operations

ICON project, 5/2019 - 4/2021

Comp4Drones

IPI contributes to a novel framework of key enabling technologies for safe and autonomous drones. We focus on hyperspectral imaging from manually flown drones for inspection of offshore turbines structure to detect imperfections, such as corrosion deterioration of paint.

ECSEL JU, 10/2019 – 9/2022

Next Perception

IPI investigates cooperative sensor fusion in support of safety and comfort at road intersections especially for vulnerable road users such as pedestrians and bikers

ECSEL JU, 5/2020 – 4/2023

Vision-in-the-loop

The VIL project aims to improve print quality, reduce waste, and cut the cost of additive metal manufacturing

ICON project, 4/2020 - 3/2022

News

Simon Van den Bossche featured in spring edition of De Vlaamse Scriptie Krant

An interactive ImageJ plugin for semi-automated image denoising in electron microscopy

Context-based analysis of urban air quality using an opportunistic mobile sensor network

A new vacancy

Keynote at AutoSens 2019

Contact