NDLI: Choosing local matching score method for stereo matching based-on polarization imaging

Content Provider	IEEE Xplore Digital Library
Author	Iqbal, M. Morel, O. Meriaudeau, F.
Copyright Year	2010
Description	Author affiliation: Laboratoire Le2i CNRS UMR 5158, Université de Bourgogne, 12 , Rue de la Fonderie, 71200 Le Creusot, France (Morel, O.; Meriaudeau, F.) \|\| Gunadarma University, Indonesia (Iqbal, M.)
Abstract	Polarization imaging is a powerful tool to observe hidden information from an observed object. It has significant advantages, such as computational efficiency (it only needs gray scale images) and can be easily applied by adding a polarizer in front of a camera. Many researchers used polarization in various areas of computer vision, such as object recognition, segmentation and so on. However, there is very little research in stereo vision based on polarization. Stereo vision is a well known technique for obtaining depth information from pairs of stereo digital images. One of the main focuses of research in this area is to get accurate stereo correspondences. In our work, we will study and develop a stereoscopic prototype that combines stereo vision and polarization imaging. This paper presents improved results in image acquisition, scene analysis, polarimetric calibration, and finding the best local matches between two stereo images.
Starting Page	334
Ending Page	338
File Size	250718
Page Count	5
File Format	PDF
ISBN	9781424455850
e-ISBN	9781424455867
DOI	10.1109/ICCAE.2010.5451536
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-02-26
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Polarization Computer vision Stokes Parameter Digital images Stereo matching Local Matching Object recognition Image segmentation Focusing Prototypes Polarization Imaging Cameras Stereo vision Computational efficiency
Content Type	Text
Resource Type	Article

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