Abstract

Facial skin pigmentation is one of the most prominent visible features of skin aging and often affects perception of health and beauty. To date, facial pigmentation has been evaluated using various image analysis methods developed for the cosmetic and esthetic fields. However, existing methods cannot provide precise information on pigmented spots, such as variations in size, color shade, and distribution pattern. The purpose of this study is the development of image evaluation methods to analyze individual pigmented spots and acquire detailed information on their age-related changes. To characterize the individual pigmented spots within a cheek image, we established a simple object-counting algorithm. First, we captured cheek images using an original imaging system equipped with an illumination unit and a high-resolution digital camera. The acquired images were converted into melanin concentration images using compensation formulae. Next, the melanin images were converted into binary images. The binary images were then subjected to noise reduction. Finally, we calculated parameters such as the melanin concentration, quantity, and size of individual pigmented spots using a connected-components labeling algorithm, which assigns a unique label to each separate group of connected pixels. The cheek image analysis was evaluated on 643 female Japanese subjects. We confirmed that the proposed method was sufficiently sensitive to measure the melanin concentration, and the numbers and sizes of individual pigmented spots through manual evaluation of the cheek images. The image analysis results for the 643 Japanese women indicated clear relationships between age and the changes in the pigmented spots. We developed a new quantitative evaluation method for individual pigmented spots in facial skin. This method facilitates the analysis of the characteristics of various pigmented facial spots and is directly applicable to the fields of dermatology, pharmacology, and esthetic cosmetology.

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