Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Shadow-invariant classification for scenes illuminated by daylight.

J A Marchant1, C M Onyango

  • 1Image Analysis and Control Group, Silsoe Research Institute, Bedford, UK. john.marchant@bbsrc.ac.uk

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|November 4, 2000
PubMed
Summary

This study introduces a physics-based shadow compensation method for daylight images. It transforms image ratios to create a shadow-independent classification, improving outdoor scene analysis.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Color invariant for daylight changes: relaxing the constraints on illuminants.

Journal of the Optical Society of America. A, Optics, image science, and vision·2001
Same author

Improving free play skills of severely retarded children.

The American journal of occupational therapy : official publication of the American Occupational Therapy Association·1978
See all related articles

Area of Science:

  • Computer Vision
  • Image Processing
  • Physics-based Rendering

Background:

  • Shadows in daylight scenes complicate image analysis and classification.
  • Existing methods may struggle with varying illumination conditions and surface reflectivities.

Purpose of the Study:

  • To develop a robust shadow compensation technique for daylight-illuminated scenes.
  • To enable shadow-independent image classification by transforming image data.

Main Methods:

  • A physics-based approach utilizing simplified blackbody radiation and CIE daylight models.
  • Mathematical transformation of red/blue (rm) and green/blue (gm) ratios into a power law relationship.
  • Pre-calculation of the exponent 'A' based on camera filter characteristics and daylight models.

Related Experiment Videos

Main Results:

  • Demonstrated that the power law relationship holds even with finite camera bandwidths and the CIE daylight model.
  • Transformed images showed similar gray-level distributions for shadowed and non-shadowed areas.
  • Thresholding transformed images yielded effective shadow-independent classifications.

Conclusions:

  • The proposed method provides effective shadow compensation in outdoor images.
  • The transformation enables reliable image classification irrespective of shadow presence.
  • This technique enhances the analysis of scenes with complex lighting.