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This page contains the list of events planned within the framework of ACROSS, including but not limited to upcoming conferences, workshops, invited and special sessions, round tables, and events oriented towards raising awareness about the project and its achievements in general public.

Published: 2014-05-21 at 18:47
Colloquium "Detection of...

The Centre of Research Excellence for Advanced Cooperative Systems (ACROSS) invites you to the joint colloquium of ACROSS and VISTA project

"Detection of Roadside Vegetation Using Features from the Visible Spectrum"

held by Iva Harbaš, mag. ing.

Colloquium details
Title Detection of Roadside Vegetation Using Features from the Visible Spectrum
Speakers Iva Harbaš, mag. ing.
Date 23. 5. 2014. 14:15 - 15:00
Location Faculty of Electrical Engineering and Computing, TCR

More about the speaker and colloquium can be found in the detailed news content.


Detection of vegetation in images is a common procedure in remote sensing and is commonly applied to satellite and aerial images. Recently it has been applied to images recorded from within ground vehicles for autonomous navigation in outdoor environments. In this presentation we present our research in detecting roadside vegetation which is intended for traffic safety and infrastructure maintenance. While many published methods for vegetation detection are using Near Infrared images which are particularly suitable for vegetation detection, our method uses image features from the visible spectrum allowing the use of common on-board color camera. Our feature set consists of color features and texture features. One of our specific goals was to identify a useful texture feature set for the problem of vegetation detection. Based on the feature set, the detection is implemented using a Support Vector Machine algorithm. For training and testing purposes we recorded our own image database consisting of different images containing roadside vegetation in various conditions. We are presenting promising experimental results and a discussion of specific problems experienced or expected in real-world application of the method.


Iva Harbaš received her BSc and MSc degree from the Faculty of Electrical Engineering and Computing in Zagreb. She finished her undergraduate study program in Computing in 2010 with a specialization in Information Processing and Multimedia Systems and in 2012 she finished her master study program in Information and Communication Technology specializing in Information Processing. Currently,  she is employed at the Faculty of Electrical Engineering and Computing, University of Zagreb, as a research engineer at the Department of Electronic Systems and Information Processing, where she is pursuing her PhD degree. Her research interests are in the area of image processing and application of machine learning methods for solving problems in computer vision.

Mario Bukal
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ACROSS project has received research funding from the Seventh Framework Programme of the European Union (Grant Agreement No. 285939 FP7-REGPOT-2011-1).


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