Mario Valerio Giuffrida, Giovanni Maria Farinella, Sebastiano Battiato, Mirko Guarnera

Three-Dimensional Image Processing, Measurement (3DIPM), and Applications (2015)

Mario Valerio Giuffrida, Giovanni Maria Farinella, Sebastiano Battiato, and Mirko Guarnera “Exploiting time-multiplexing structured light with picoprojectors”, Proc. SPIE 9393, Three-Dimensional Image Processing, Measurement (3DIPM), and Applications, 939304 (2015)

Giuffrida et al. (2015)
Open Externally
author = {Mario Valerio Giuffrida and Giovanni Maria Farinella and Sebastiano Battiato and Mirko Guarnera},
title = {{Exploiting time-multiplexing structured light with picoprojectors}},
volume = {9393},
booktitle = {Three-Dimensional Image Processing, Measurement (3DIPM), and Applications 2015},
editor = {Robert Sitnik and William Puech},
organization = {International Society for Optics and Photonics},
publisher = {SPIE},
pages = {19 -- 31},
keywords = {Structured light, Picoprojector, Gray code patterns, Time-multiplexing},
year = {2015},
doi = {10.1117/12.2083031},
URL = {}


When a picture is shot all the information about the distance between the object and the camera gets lost. Depth estimation from a single image is a notable issue in computer vision. In this work we present a hardware and software framework to accomplish the task of 3D measurement through structured light. This technique allows to estimate the depth of the objects, by projecting specific light patterns on the measuring scene. The potentialities of the structured light are well-known in both scientific and industrial contexts. Our framework uses a picoprojector module provided by STMicroelectronics, driven by the designed software projecting time- multiplexing Gray code light patterns. The Gray code is an alternative method to represent binary numbers, ensuring that the hamming distance between two consecutive numbers is always one. Because of this property, this binary coding gives better results for depth estimation task. Many patterns are projected at different time instants, obtaining a dense coding for each pixel. This information is then used to compute the depth for each point in the image. In order to achieve better results, we integrate the depth estimation with the inverted Gray code patterns as well, to compensate projector-camera synchronization problems as well as noise in the scene. Even though our framework is designed for laser picoprojectors, it can be used with conventional image projectors and we present the results for this case too.