Stereo matching technique based on the perceptron criterion function
Pattern Recognition Letters
A neural network model in stereovision matching
Neural Networks
Stereo matching based on the self-organizing feature-mapping algorithm
Pattern Recognition Letters
Active Computer Vision by Cooperative Focus and Stereo
Active Computer Vision by Cooperative Focus and Stereo
Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Image Processing - Principles and Applications
Image Processing - Principles and Applications
3D Terrain Modeling for Rover Localization and Navigation
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
Interested Sample Point Pre-Selection Based Dense Terrain Reconstruction for Autonomous Navigation
IITA '09 Proceedings of the 2009 Third International Symposium on Intelligent Information Technology Application - Volume 03
Leaving flatland: toward real-time 3D navigation
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Stereo vision for robotic applications in the presence of non-ideal lighting conditions
Image and Vision Computing
3D Terrain Reconstruction for Patrol Robot Using Point Grey Research Stereo Vision Cameras
AICI '10 Proceedings of the 2010 International Conference on Artificial Intelligence and Computational Intelligence - Volume 01
Computational Experiments with a Feature Based Stereo Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Novel mean-shift based histogram equalization using textured regions
Expert Systems with Applications: An International Journal
Efficient stereo image rectification method using horizontal baseline
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part I
Epipolar line estimation and rectification for stereo image pairs
IEEE Transactions on Image Processing
| Hi-index | 12.05 |
This paper proposes an automatic expert system for 3D terrain reconstruction and automatic intensity correction in stereo pairs of images based on histogram matching. Different applications in robotics, particularly those based on autonomous navigation in rough and natural environments, require a high-quality reconstruction of the surface. The stereo vision system is designed with a defined geometry and installed onboard a mobile robot, together with other sensors such as an Inertial Measurement Unit (IMU), necessary for sensor fusion. It is generally assumed the intensities of corresponding points in two images of a stereo pair are equal. However, this assumption is often false, even though they are acquired from a vision system composed of two identical cameras. We have also found this issue in our dataset. Because of the above undesired effects the stereo matching process is significantly affected, as many correspondence algorithms are very sensitive to these deviations in the brightness pattern, resulting in an inaccurate terrain reconstruction. The proposed expert system exploits the human knowledge which is mapped into three modules based on image processing techniques. The first one is intended for correcting intensities of the stereo pair coordinately, adjusting one as a function of the other. The second one is based in computing disparity, obtaining a set of correspondences. The last one computes a reconstruction of the terrain by reprojecting the computed points to 2D and applying a series of geometrical transformations. The performance of this method is verified favorably.