Videos are one of the main multimedia files available to public on the internet thanks to the giant free web-hosting companies (e.g., YouTube, Google Videos, etc). Every day a mass of these files is uploadedonline andhuman factors areusually present. Usage of the transformation is twofold; first to segment homogeneous objects in the cover image namely human skin regions in this study, and second to embed our data using the red chrominance (Cr). The YCbCr space can remove the correlation of R, G, and B in a given image. This phenomenon is what interests us as less correlation between colours means less noticeable distortion. In our approach, the concentration on skin tone is motivated by some interesting applications of the final product. For instance, to combat the use of forged passport documents or national identity cards, a security measure would be to embed individuals’ information in their photos. This can also reduce the cost of chip production since many contemporary identity cards use chips. Moreover, it enhances portability as the decoding phase can take place anywhere using a tiny applet application installed on mobile devices. There are different algorithms exploiting different colour spaces to detect human skin tone in colour images [12,14]. YCbCrRGB o Our algorithm starts first with the segmentation of probablehuman skin regions: