Using industrial cameras and multispectral imaging technology to implement medical beauty skin AI detection application solutions
As young people have higher and higher requirements for skin management,"Technical skin care" has become offlineMedicalUpgrade trend.How to use advanced image recognition technology and big data analysis to provide doctors and consumers with personalized skin diagnostic analysis and skin care advice, and use industrial cameras and multispectral imaging technology to perfectly achieve this possibility.
What is multispectral imaging
Multi-spectral imaging refers to using multiple (as many as dozens) spectral bands to measure an object and convert the measured information signal into a multi-level spectral image to provide more accurate information.The principle is that multispectral images can capture information about potential matter and materials and can help extract features.In fact, ground materials in each band have specific spectral reflection characteristics; it is through the combined image of multiple numerical bands that can perform multi-dimensional analysis of the characterized substances on the object surface to calculate the information required by various reflection characteristics and vegetation geometric structures.
Application of multi-spectral in skin detection
The color of normal human skin is determined by a series of interconnected factors, and melanin is the most important factor.Because it is affected by factors such as genes, hormones and sunlight, it changes the amount of pigmentation in the epidermis.Skin pigments, hemoglobin, melanin and other lesions have different degrees of absorption properties on incident light, and it is extremely important to select matching specific spectra to improve their visibility and contrast.Generally, when observing skin melaninated melasma lesions, the wavelength should be selected for the wavelength of 400-450nm when observing skin melaninated images, and when dilated or bleeding spots, the wavelength should be selected for skin capillaries, which can improve the contrast between normal skin and lesions and make the image clearer.
Skin image analysis system working principle schematic circleReal-time grayscale measurement in points, lines, surfaces, and any area of the measurement target; histogram measurement; skin lesions and non-skin lesions images were measured respectivelyRGBThe grayscale, average optical density, optical density, integrated optical density target area and other stereoscopic parameters point counting, surface density, number density, volume density, group ratio and general commonly used statistical processing of each frame body.UseMulti-spectral skin micropolarized light and digital image processing technology can measure the changes in target lesions shape, area, grayscale, integral optical density and pigment color parameters.
