Developing a visual stopping criterion for image mosaicing using invariant color histograms

Armagan Elibol, Hyunjung Shim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


For over a decade, image mosaicing techniques have been widely used in various applications e.g., generating a wide field-of-view image, 2D optical maps in remote sensing or medical imaging. In general, image mosaicing combines a sequence of images into a single image referred to as a mosaic image. Its process is roughly divided into the iterative image registration and blending. Unfortunately, the computational cost of iterative image registration increases exponentially given a large number of images. As a result, mosaicing for a large scale scene is often prohibitive for real-time applications. In this paper, we introduce an effective visual criterion to reduce the number of image mosaicing iterations while retaining the visual quality of the mosaic. We analyze the change in invariant color histograms of the mosaic image over iterations and use it to determine a termination condition. Based on various experimental evaluations using four different datasets, we significantly improve the computational efficiency of mosaicing algorithm.

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing – PCM 2015 - 16th Pacific-Rim Conference on Multimedia, Proceedings
EditorsYo-Sung Ho, Yong Man Ro, Junmo Kim, Fei Wu, Jitao Sang
PublisherSpringer Verlag
Number of pages10
ISBN (Print)9783319240770
Publication statusPublished - 2015
Event16th Pacific-Rim Conference on Multimedia, PCM 2015 - Gwangju, Korea, Republic of
Duration: 2015 Sept 162015 Sept 18

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other16th Pacific-Rim Conference on Multimedia, PCM 2015
Country/TerritoryKorea, Republic of

Bibliographical note

Funding Information:
Authors would like to thank Underwater Vision Laboratory of Computer Vision and Robotics Institute of University of Girona for providing high-resolution test images and real trajectory parameters. This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Republic of Korea, under the IT Consilience Creative Program (NIPA-2014-H0201-14-1002) supervised by the NIPA (National IT Industry Promotion Agency). Aerial High-resolution image was retrieved from on the 27th of April, 2015.

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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