Analysis of Methods for Extraction of Information on Images with Low-Depth of Field

Paper #:
  • 2015-36-0225

Published:
  • 2015-09-22
DOI:
  • 10.4271/2015-36-0225
Citation:
de Luca, F. and Thomaz, C., "Analysis of Methods for Extraction of Information on Images with Low-Depth of Field," SAE Technical Paper 2015-36-0225, 2015, https://doi.org/10.4271/2015-36-0225.
Affiliated:
Pages:
12
Abstract:
In order to make devices partially or completely autonomous, it is imperative nowadays to extract relevant information from the myriad of data available. In the last years, it has become very common to use images as signals of interest to propose feasible solution to this problem. Image recognition can be used with high accuracy rates when the object of interest or the environment are controlled or well known. However, in open urban spaces, for instance, where there are all sorts of visual artifacts and stimuli (information), the segmentation of the object of interest (foreground) from the rest of the image (background) is a challenging issue. One possible way to tackle this problem is to use low-depth of field images, which analogously to our visual perception highlight the object of interest from the rest of the image. In this work, some methods and algorithms for segmenting low-depth of field images are analyzed and compared, providing an updated and contextualized version of the state-of-the-art of this topic.
Access
Now
SAE MOBILUS Subscriber? You may already have access.
Buy
Select
Price
List
Download
$27.00
Mail
$27.00
Members save up to 40% off list price.
Share
HTML for Linking to Page
Page URL

Related Items

Standard
2011-06-01
Training / Education
2016-03-07
Technical Paper / Journal Article
2011-04-12
Technical Paper / Journal Article
2010-04-12