Cullets optical sorting represents one of the oldest selection procedure applied to the field of solid waste recycling. From the original sorting strategies, mainly addressed to separate non-transparent elements (ceramics, stones, metal particles, etc.) from transparent ones (glass fragments), the attention was addressed to define procedures and actions able to separate the cullets according to their color characteristics and, more recently, to recognize transparent ceramic glass from glass. Cullets sorting is currently realized adopting, as detecting architecture, laser beam technology based devices. The sorting logic is mainly analogical. An “on-off” logic is applied. Detection is, in fact, based on the evaluation of the “characteristics” of the energy (transparent or non-transparent fragment) and the spectra (fragment color attributes) received by a detector after that cullets were crossed by a suitable laser beam light. Such an approach presents some limits related with the technology utilized and the material characteristics. The technological limits are linked to the physical dimension and the mechanical arrangement of the optics carrying out and in the signals, and with the pneumatic architectures enabling the modification of cullets trajectory to realize sorting, according to their characteristics (color and transmittance). Furthermore such devices are practically “blind” in the recognition of ceramic glasses, whose presence in the final selected material to melt, damage the full recycled glass fusion compromising the quality of the final product. In the following it will be described the work developed, and the results achieved, in order to design a full integrated classical digital imaging and spectrophotometric based approach addressed to develop suitable sorting strategies able to perform, at industrial recycling scale, the distinction of cullets both in terms of color and material typologies, that is “real glass” from “ceramic glass” fragments.