๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Particle depth measurement based on depth-from-defocus

โœ Scribed by Shigeru Murata; Masayoshi Kawamura


Book ID
104160370
Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
451 KB
Volume
31
Category
Article
ISSN
0030-3992

No coin nor oath required. For personal study only.

โœฆ Synopsis


An optical and digital method has been developed for the detection of the depth of small particles distributed in 3D space and its performance has been examined in numerical simulations and experiments. The present method is based on depth-fromdefocus in which the depth of particle is detected from the image blur of the particle. The results of numerical simulations show that low-pass ยฎltering is eective for the reduction of error. In the experiments with a single 3CCD color camera, it is found that the RMS error of the present method is 1.81 mm for the depth range of 40 mm.


๐Ÿ“œ SIMILAR VOLUMES


A video-rate range sensor based on depth
โœ Ovidiu Ghita; Paul F Whelan ๐Ÿ“‚ Article ๐Ÿ“… 2001 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 870 KB

Recovering the depth information derived from dynamic scenes implies real-time range estimation. This paper addresses the implementation of a bifocal range sensor which estimates the depth by measuring the relative blurring between two images captured with di erent focal settings. To recover the dep

On defocus, diffusion and depth estimati
โœ Vinay P. Namboodiri; Subhasis Chaudhuri ๐Ÿ“‚ Article ๐Ÿ“… 2007 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 739 KB
Depth from Defocus Estimation in Spatial
โœ Djemel Ziou; Francois Deschenes ๐Ÿ“‚ Article ๐Ÿ“… 2001 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 509 KB

This paper presents an algorithm for a dense computation of the difference in blur between two images. The two images are acquired by varying the intrinsic parameters of the camera. The image formation system is assumed to be passive. Estimation of depth from the blur difference is straightforward.