Some of the first home movies in color were shot on 16 mm lenticular film during the 1920s to 1940s. This very special film is embossed with a vertical array of hundreds of tiny cylindrical lenses that allowed to record color scenes on a black&white silver emulsion. The most efficient approach to obtain digital color images from these historical motion pictures is to scan the silver emulsion in high-
resolution and let a software extract the encoded color information. The present work focuses on the localization of the lenticular screen, which is the first and most complicated step of the color reconstruction. A ‘classic’ signal processing method proved to deliver successful results in some cases, but often adverse factors—damaged or warped film, scanning problems—hinder the successful localization of the lenticular screen. Deep-doLCE explores a more advanced and robust method, using a big dataset of digitized lenticular films to train a new deep learning software. The aim is to create an easy-to-use software that revives awareness of the lenticular color processes thus making these precious historical color movies available again to public and securing them for posterity.