Taking Advantage of Selective Change Driven Processing for 3D Scanning

Abstract

This article deals with the application of the principles of SCD (Selective Change Driven) vision to 3D laser scanning. Two experimental sets have been implemented: one with a classical CMOS (Complementary Metal-Oxide Semiconductor) sensor, and the other one with a recently developed CMOS SCD sensor for comparative purposes, both using the technique known as Active Triangulation. An SCD sensor only delivers the pixels that have changed most, ordered by the magnitude of their change since their last readout. The 3D scanning method is based on the systematic search through the entire image to detect pixels that exceed a certain threshold, showing the SCD approach to be ideal for this application. Several experiments for both capturing strategies have been performed to try to find the limitations in high speed acquisition/processing. The classical approach is limited by the sequential array acquisition, as predicted by the Nyquist–Shannon sampling theorem, and this has been experimentally demonstrated in the case of a rotating helix. These limitations are overcome by the SCD 3D scanning prototype achieving a significantly higher performance. The aim of this article is to compare both capturing strategies in terms of performance in the time and frequency domains, so they share all the static characteristics including resolution, 3D scanning method, etc., thus yielding the same 3D reconstruction in static scenes.

Sensors and Technologies in Spain: State-of-the-Art

“…A 3D laser and CMOS-vision scanner is the device proposed in [ 67 ] for determining 3D measurements. Based on the well-known active triangulation principle, the laser projects a pattern on the surface to be measured, this pattern is captured on the focal plane of the camera, where applying triangulation the depth of the surface is obtained.…”

A Selective Change Driven System for High-Speed Motion Analysis

“…It has been already proven, with the previous 32 × 32 SCD sensor based on an integration cell, that this approach can be employed to detect the frequency of a rotating movement at very high speeds [32]. In this study, movement detection is done off-line by software in a PC (with the Fourier transform), due to the relatively long delay of the data in the order of tenths of $\mathrm{sans-serif\mu }$s.…”