Anonymization methods are one potential way of alleviating the risks of capturing personal information during data collections. The work presented here is based on one such method that, in turn, is based on generating images through machine learning to replace the original images. The chosen method merges both the original image and the generated one resulting in a risk of information from the original image leaking through to the final result. Here a possible approach to measure how much influence the original image has on the final product is presented .