It includes significant representations of Black, White, Hispanic, Asian, and "Other" ethnicities.
Because MORPH II has a significant representation of different ethnicities (particularly Black and White subjects), it is frequently used to test if an algorithm performs equitably across different races. How to Access Verified Data
A explicitly corrects these issues before training begins: 1. Conflicting Age and Birthdate Records
The MORPH II dataset is a cornerstone in biometric research, particularly for longitudinal studies in facial recognition and age estimation. While often cited for its scale, achieving a or "cleaned" version of this data is a critical task for researchers due to inherent inconsistencies in the original raw collection. Overview of the MORPH II Dataset morph ii dataset verified
"While the Morph II dataset is widely used and has been verified for basic integrity (e.g., no duplicate images, correct subject IDs), its limitations in demographic diversity and controlled capture conditions mean that 'verified' does not automatically make it suitable for all face recognition benchmarks."
Because MORPH-II is an academic dataset, it is not publicly distributed on open-access repositories like Kaggle. Access is restricted and granted exclusively to qualified researchers, universities, and law enforcement agencies for non-commercial, biometric research purposes.
: To ensure scientific validity, many studies utilize specific verified subsets (often denoted as S1, S2, or S3) that balance gender and racial distributions to avoid algorithmic bias. Key Dataset Statistics Total Samples Approximately 55,134 images Unique Subjects ~13,617 individuals Age Range 16 to 77 years Demographics Conflicting Age and Birthdate Records The MORPH II
Isolates images with severe discrepancies (e.g., age shifts greater than 1 year).
In unverified sets, a single individual might be assigned two different ID numbers, or two different people might be grouped under one ID. Verification involves manual or algorithmic cross-referencing to ensure that every "subject" is truly unique and consistent throughout their aging sequence. 2. Accurate Metadata
The dataset is heavily imbalanced toward . The racial breakdown is: Access is restricted and granted exclusively to qualified
Despite its status, the raw MORPH II dataset was plagued by significant . Most of the data was self-reported by individuals during booking, leading to a variety of errors that, if left unchecked, could invalidate research conclusions.
Ensure your institution has signed the necessary paperwork to use the data for non-commercial research.