Unsupervised Texture Segmentation Using Markov Random Field Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian Fusion of Color and Texture Segmentations
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A Statistical Approach to Texture Classification from Single Images
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
A Bayesian Hierarchical Model for Learning Natural Scene Categories
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
International Journal of Computer Vision
Deterministic neural classification
Neural Computation
FCTH: Fuzzy Color and Texture Histogram - A Low Level Feature for Accurate Image Retrieval
WIAMIS '08 Proceedings of the 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services
Discriminative Locality Alignment
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
CEDD: color and edge directivity descriptor: a compact descriptor for image indexing and retrieval
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Enhanced local texture feature sets for face recognition under difficult lighting conditions
IEEE Transactions on Image Processing
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers
IEEE Transactions on Robotics
Universal approximation using incremental constructive feedforward networks with random hidden nodes
IEEE Transactions on Neural Networks
Modelling and trajectory planning for a four legged walking robot with high payload
ICSR'12 Proceedings of the 4th international conference on Social Robotics
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In this paper, we present a comparison of multiple approaches to visual terrain classification for outdoor mobile robots based on different color, texture and local features. We introduce and compare three novel composite descriptors called CEDD, FCTH and JCD, with traditional color and texture descriptors, such as LTP, SCD, EHD and a descriptor called CSD-HTD generated by late fusion method. We also test three BOW models based on SIFT, SURF and ORB, respectively. We used two terrain classification datasets of which the images were captured from outdoor moving robots under different weather and ground conditions. Hence some of the images are blurred or unideally exposed. We utilize ELM, SVM and NN for classification to evaluate the performance of different combinations of image descriptors and classifiers. Experiments demonstrate that JCD can represent different terrain images with significant inter-class discrepancies, and ELM has mild optimization constraints and obtains better generalization performance. Results show that the approach based on JCD descriptor and ELM classifier performs best in term of classification effectiveness and it is suitable for real-time outdoor visual terrain classification.