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Publications

NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.

NIBIO's Scientific Publications →

2017

Authors

Inger Sundheim Fløistad Jenssen Espen Kristoffer

Abstract

No abstract has been registered

Authors

Isabella Børja Halvor Solheim Nina Elisabeth Nagy Volkmar Timmermann Ari Hietala

Abstract

No abstract has been registered

Authors

Volkmar Timmermann Nina Elisabeth Nagy Ari Hietala Isabella Børja Halvor Solheim

Abstract

No abstract has been registered

Authors

Mladen Ognjenović Ivan Seletković Volkmar Timmermann Nenad Potočić

Abstract

No abstract has been registered

Authors

Johannes Deelstra Attila Nemes Helen French

Abstract

No abstract has been registered

Authors

Johannes Rahlf

Abstract

No abstract has been registered

Authors

Björn Klimek

Abstract

No abstract has been registered

Authors

Eva Brod

Abstract

No abstract has been registered

To document

Authors

Matthias Koesling

Abstract

No abstract has been registered

To document

Authors

Ricardo Fonseca Werner Creixell Javier Maiguashca Victor Rueda-Ayala

Abstract

Image analysis is essential through a wide range of scientific areas and most of them have one task in common, i.e. object detection. Thus automated detection algorithms had generated a lot of interest. This proposal identifies objects with similar features on a frame. The inputs are the image where to look at, and a single appearance of the object we are looking for. The object is searched by a sliding window of various sizes. A positive detection is given by a cascaded classifier that compares input patches from sliding window to the object model. The cascaded classifier has three stages: variance comparison, layers of pixel comparisons and patch correlation. Object model is a collection of templates which are generated from scales and rotations of the first appearance. This algorithm is capable to handle change in scale, in plane rotation, illumination, partial occlusion and background clutter. The proposed framework was tested on high cluttered background aerial image, for identifying palm oil trees. Promising results were achieved, suggesting this is a powerful tool for remote sensing image analysis and has potential applications for a wide range of sciences which require image analysis.