A Novel Image Similarity Measure for Place Recognition in Visual Robotic Navigation

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

1 Citation (SciVal)


In this work we tackle the issue of visually recognising a place without any prior knowledge of its position, even in a world where the same place can look different or many places can look identical.
To achieve a fast and robust image similarity measure for place recognition, we use the concept of quadtree decomposition combined with a number of standard image distance measures to create a novel image similarity method. Unlike the majority of current image comparison methods that use feature extraction and matching, our approach is a direct pixel-wise comparison of two images [1] gaining robustness through the incorporation of the quadtree concept. Quadtrees not only provide a noise resistant, fast, and easy to use comparison method, but also allow us to identify those image regions that genuinely represent changes within the environment.
Original languageEnglish
Title of host publicationAdvances in Autonomous Robotics
Subtitle of host publicationLecture Notes in Artificial Intelligence
EditorsGuido Herrmann, Matthew Studley, Martin Pearson, Andrew Conn, Chris Melhuish, Mark Witkowski, Jong-Hwan Kim, Prahlad Vadakkepat
PublisherSpringer Nature
Number of pages2
ISBN (Print)978-3-642-32526-7, 3642325262
Publication statusPublished - 10 Jul 2012

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
ISSN (Print)0302-9743


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