Study On Object Measurement Of The Skin Erythema

Skin erythema is a familiar symptom in clinical dermatology. Its objective measurement is of importance in clinical dermatological diagnosis and new drug tests. This paper studies the ways to measure the skin erythema objectively.Since skin erythema covers the information of color and shape, we adopted the digital imaging way to measure it. We studied the precision of the measurement system, the measurement indexes, the way how to measure and the methods to segment the color skin erythema images.Firstly, we introduced an improved digital imaging measurement system on skin diseases and compared the HSV, Lab, RGB color space to pursue which color space is fit to measure the skin color. The result demonstrates that the HSV color space is of superiority. Then, we've corrected the HSV color space in order to suitably describe the color characteristics of skin erythema. At last, we analysed the precision of the measurement system through the computer simulation.The result suggest that there is certain connection between the precision of the measurement system and the color of the measured object.Secondly, we investigated a new parameter defined by the difference of the logarithm of the reflected light intensity between normal skin and the erythema skin to describe the pathology change of the erythema. Deducing theoretically, we can draw the conclusion that this parameter not only can reflect the deviation degree of the concentration of haemoglobin in the dermis from the normal value, but also can hardly be influenced by the melanin in the epidermis and the incident intensity. In the aspect of experimental study, we first analyzed whether this parameter can be affected by the incident intensity, and then we applied it to the clinic and traced the effect of curing skin erythema.Thirdly, we adopted the FCM arithmetic to segment the color skin erythema images and e proposed K (k=s/h, h is hue, s is saturation of HSV color space) as the segmentation feature parameter. By comparing the effect and the speed of the segmentation when the k and other three segmentations feature were employed, we found that the result by choosing K as the segmentation feature parameter is better.