Hair counting method based on image processing technology

Abstract

The number of hair per unit area of scalp is an important indicator of hair growth. In order to realize the understanding of head fur growing condition, this paper designs a hair counting method based on image processing technology. The color characteristics of the high definition scalp hair images taken by light microscope were analyzed and the Wright test was used to eliminate the shadow and subtle hair interference. Then the original image was preprocessed and pieceby-linear transformation was enhanced, and then the threshold segmentation was performed to extract the hair root image, and a single scalp hair image was counted, and the scalp hair counting function model was constructed to realize the scalp hair counting in the whole region. Analysis shows that the experimental results accord with the physiological characteristics of hair growth, and the method can avoid most of the noise interference of hair image, and meet the actual requirements of scalp hair counting.