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



Downloads per month over past year

Herrera, Pedro Javier and Pajares Martinsanz, Gonzalo and Guijarro Mata-García, María and Ruz Ortíz, José Jaime and Cruz, Jesús M. (2011) A Stereovision Matching Strategy for Images Captured with Fish-Eye Lenses in Forest Environments. Sensors, 11 (2). pp. 1756-1783. ISSN 1424-8220

[thumbnail of sensors-11-01756.pdf]
Creative Commons Attribution.


Official URL: https://doi.org/10.3390/s110201756


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.

Item Type:Article
Uncontrolled Keywords:fish-eye stereovision matching; fuzzy clustering; Bayesian classifier; weighted fuzzy similarity; Hopfield neural networks; texture classification; fish-eye lenses; hemispherical forest images
Subjects:Sciences > Computer science > Artificial intelligence
Sciences > Computer science > Networks
Sciences > Computer science > Expert systems (Computer science)
ID Code:68481
Deposited On:03 Nov 2021 11:33
Last Modified:03 Nov 2021 12:15

Origin of downloads

Repository Staff Only: item control page