Skip to main content

Near infrared photography for craniofacial anthropometric landmark measurement

Buy Article:

$43.00 plus tax (Refund Policy)


Photogrammetry has been recognised as an essential tool for the capture of spatial data to populate a craniofacial spatial database. A craniofacial database aims to provide medical practitioners with accurate craniofacial measurements for medical applications such as craniofacial reconstruction. New technologies and improved techniques continue to be developed to capture accurate spatial data of normal craniofacial features as well as the abnormal (malformations and victims of disease, trauma and burns). Digital near infrared (NIR) cameras are becoming more widely available. The resulting images have a number of advantages over traditional colour photographs. In particular, NIR cameras operate well in low light environments because they provide their own NIR light source. Consequently, this research was carried out to determine the suitability of NIR photography for craniofacial spatial data capture.

The paper provides a discussion of the laboratory testing, data analysis and results of the use of NIR photography for automated and manual craniofacial spatial data capture in various lighting environments. The results show that the automated measurement accuracy is similar for both NIR and colour photographs. No specific signalised targets were needed for the camera calibration of NIR data-sets. Also, the research found that NIR photographs provide higher contrast compared to colour photographs for manual stereodigitising of anthropometric landmarks when the photographs were taken in a faint-lighting environment. Consequently, the research suggests that the NIR photographs could be used as an alternative to colour photographs for craniofacial spatial data capture.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Keywords: anthropometric landmarks; camera calibration; close range digital photogrammetry; craniofacial features; near infrared imagery

Document Type: Research Article

Affiliations: 1: ( ), Email: [email protected] 2: ( ) University of Otago, New Zealand, Email: [email protected]

Publication date: 2006-03-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more