A novel skin pigment separation method based on sub-block selection and local clustering.

ABSTRACT:

Background

Skin pigment separation is a key task in the fields of medical aesthetics, clinical analysis, and dermatological diagnosis. Existing pigment separation methods suffer from the problem of unclear separation between melanin and hemoglobin.

Methods

This study proposes a novel approach that combines a sub-block selection algorithm with local clustering for skin pigment separation. The sub-block selection algorithm sorts and filters sub-blocks based on the average pixel difference, reconstructing the input data to ensure accurate separation of melanin and hemoglobin. The local clustering method uses the Euclidean distance between sample points and their surrounding cluster centers to assign sample points to their respective clusters. A random sampling of sample points

SUBMITTER: Yang H 

PROVIDER: S-EPMC12520397 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature