This paper presents a new efficient technique for supervised pixel-based texture classification. The proposed scheme first performs a selection process that automatically determines a subset of prototypes that charact...
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ISBN:
(纸本)9781424456536
This paper presents a new efficient technique for supervised pixel-based texture classification. The proposed scheme first performs a selection process that automatically determines a subset of prototypes that characterize each texture class based on the outcome of a multichannel Gabor wavelet filter bank. Then, every image pixel is classified into one of the given texture classes by using a K-NN classifier fed with the prototypes determined previously. The proposed technique is compared to previous texture classifiers by using both Brodatz and real outdoor textured images.
This paper describes a new technique for determining the distance to a planar surface and, at the same time, obtaining a characterization of the surface's material through the use of conventional, low-cost infrare...
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Texture-based pixel classification has been traditionally carried out by applying texture feature extraction methods that belong to a same family (e.g., Gabor filters). However, recent work has shown that such classif...
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Recent advances in the understanding of animal locomotion have proven it to be a key element of many fields in biology, motion science, and robotics. For the analysis of walking animals, high-speed x-ray videography i...
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A wide variety of texture feature extraction methods have been proposed for texture based image classification and segmentation. These methods are typically evaluated over windows of the same size, the latter being us...
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This paper presents and evaluates a pixel-based texture classifier that integrates multiple texture feature extraction methods through a new scheme based on the Kullback J-divergence. Experimental results show that th...
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This paper proposes a pixel-based texture classifier that integrates multiple texture feature extraction methods in order to identify the regions of an input image that belong to a given set of texture patterns. Exper...
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This paper proposes a pixel-based texture classifier that integrates multiple texture feature extraction methods in order to identify the regions of an input image that belong to a given set of texture patterns. Exper...
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Many robotics tasks require autonomous exploration by teams of robots. In difficult or large environments, communication drop-out complicates this task. Several approaches exist that aim to keep the team connected, bu...
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ISBN:
(纸本)9780980740424
Many robotics tasks require autonomous exploration by teams of robots. In difficult or large environments, communication drop-out complicates this task. Several approaches exist that aim to keep the team connected, but even so there is an inherent limit to the range that can be explored. In this paper we describe and examine Role-Based Exploration, an approach that uses mobile relays to ferry information back and forth within the team, and compare it to methods that do not. There are significant advantages in the use of such relays, such as improved coordination and responsiveness, and adaptability to unexpected communication dropout. The approaches are implemented and validated on a team of real robots.
Deep neural networks virtually dominate the domain of most modern vision systems, providing high performance at a cost of increased computational complexity. Since for those systems it is often required to operate bot...
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