Next Article in Journal
Next Article in Special Issue
Previous Article in Journal
Previous Article in Special Issue
Sensors 2011, 11(2), 1756-1783; doi:10.3390/s110201756
Article

A Stereovision Matching Strategy for Images Captured with Fish-Eye Lenses in Forest Environments

1,* , 2
, 2
, 1
 and 1
Received: 21 December 2010; in revised form: 12 January 2011 / Accepted: 27 January 2011 / Published: 31 January 2011
(This article belongs to the Special Issue Sensors in Agriculture and Forestry)
View Full-Text   |   Download PDF [673 KB, uploaded 21 June 2014]   |   Browse Figures
Abstract: We present a novel strategy for computing disparity maps from hemispherical stereo images obtained with fish-eye lenses in forest environments. At a first segmentation stage, the method identifies textures of interest to be either matched or discarded. This is achieved by applying a pattern recognition strategy based on the combination of two classifiers: Fuzzy Clustering and Bayesian. At a second stage, a stereovision matching process is performed based on the application of four stereovision matching constraints: epipolar, similarity, uniqueness and smoothness. The epipolar constraint guides the process. The similarity and uniqueness are mapped through a decision making strategy based on a weighted fuzzy similarity approach, obtaining a disparity map. This map is later filtered through the Hopfield Neural Network framework by considering the smoothness constraint. The combination of the segmentation and stereovision matching approaches makes the main contribution. The method is compared against the usage of simple features and combined similarity matching strategies.
Keywords: fish-eye stereovision matching; fuzzy clustering; Bayesian classifier; weighted fuzzy similarity; Hopfield neural networks; texture classification; fish-eye lenses; hemispherical forest images fish-eye stereovision matching; fuzzy clustering; Bayesian classifier; weighted fuzzy similarity; Hopfield neural networks; texture classification; fish-eye lenses; hemispherical forest images
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Herrera, P.J.; Pajares, G.; Guijarro, M.; Ruz, J.J.; Cruz, J.M. A Stereovision Matching Strategy for Images Captured with Fish-Eye Lenses in Forest Environments. Sensors 2011, 11, 1756-1783.

AMA Style

Herrera PJ, Pajares G, Guijarro M, Ruz JJ, Cruz JM. A Stereovision Matching Strategy for Images Captured with Fish-Eye Lenses in Forest Environments. Sensors. 2011; 11(2):1756-1783.

Chicago/Turabian Style

Herrera, Pedro Javier; Pajares, Gonzalo; Guijarro, María; Ruz, José J.; Cruz, Jesús M. 2011. "A Stereovision Matching Strategy for Images Captured with Fish-Eye Lenses in Forest Environments." Sensors 11, no. 2: 1756-1783.



Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert