Recognition of children on age-different images: Facial morphology and age-stable features

Zuzana Caplova1, Valentina Compassi1, Silvio Giancola2

  • 1Università degli Studi di Milano, Dipartimento di Scienze Biomediche per la Salute, Via Mangiagalli 31, 20133 Milano, Italy.

Insights

Facial features change as children grow, complicating identification. However, moles remain stable over time and can aid in recognizing missing children through facial recognition technology.

Area of Science:

  • Forensic Science
  • Anthropology
  • Computer Science

Background:

  • Missing children identification is a global challenge, often hindered by changing facial morphology over time.
  • Surveillance systems offer potential image data for comparison, but facial changes complicate identification.

Purpose of the Study:

  • To determine if facial features remain stable over time for facial recognition.
  • To evaluate the utility of moles as age-stable features for child identification.

Main Methods:

  • Morphological classification of facial features using an Anthropological Atlas.
  • Development of a MATLAB algorithm to assess moles as age-stable recognition features.

Main Results:

  • High observer mismatch percentages were found when classifying facial features using atlases.
  • Features describing shape showed lower mismatch rates than those describing size.
  • The nose tip cleft and chin dimple demonstrated the best observer agreement for categorization and stability.
  • Using mole positions as reference points proved objective and useful for recognition.

Conclusions:

  • Moles are age-stable facial features valuable for preliminary recognition of missing children.
  • Facial recognition methods incorporating mole analysis can enhance identification efforts.