In recent years, more and more researchers' attention has been drawn to the sparse representation-based classification (SRC) method and its application in image analysis and pattern recognition, due to its good characteristics of high recognition rate, robustness to corruption and occlusion, and little dependence on the features selection etc. However, sufficient training samples are always req...

This paper presents an improved local ternary pattern (LTP) for automatic target recognition (ATR) in infrared imagery. Firstly, a robust LTP (RLTP) scheme is proposed to overcome the limitation of the original LTP for achieving the invariance with respect to the illumination transformation. Then, a soft concave-convex partition (SCCP) is introduced to add some flexibility to the original conca...

Automatic target recognition (ATR) of synthetic aperture radar (SAR) image is investigated. One feature extraction algorithm of SAR image based on multilayer auto-encoder is proposed. The method makes use of a probabilistic neural network, restricted Boltzmann machine (RBM), modeling probability distribution of environment. Through the formation of more expressive multilayer neural network, the...

Automatic Term Recognition focuses on the extraction of words and multi-word expressions that are significant for a given domain. There is a considerable interest in using ATR for automatic metadata generation, creation of thesauri and terminological glossaries, keyword extraction, ontology building, etc. In this paper, we build upon the work done at the University of Sheffield, where a library...

This paper introduces an Automatic Target Recognition (ATR) method based on X Band Radar image processing. A software which implements this method was developed following four principal stages: digital image formation, image preprocessing, feature selection through a combination of C4.5 Decision Tree and PCA and classification using SVM. The automatic process was validated using two images sets...

The capability to exploit multiple sources of information is of fundamental importance in a battlefield scenario. Information obtained from different sources, and separated in space and time, provides the opportunity to exploit diversities to mitigate uncertainty. In this study, the authors address the problem of automatic target recognition (ATR) from synthetic aperture radar platforms. The au...

In this paper, a new 1-D hybrid Automatic Target Recognition (ATR) algorithm is developed for sequential High Range Resolution (HRR) radar signatures. The proposed hybrid algorithm combines Eigen-Template based Matched Filtering (ETMF) and Hidden Markov modeling (HMM) techniques to achieve superior HRR-ATR performance. In the proposed hybrid approach, each HRR test profile is first scored by ET...

This paper investigates a template-matching approach to automatic target recognition (ATR) for SAR for the case in which positive identification of a single known target type is required. ATR schemes are necessarily supported by databases of training imagery and of particular interest in this study was the impact on performance of using a database of simulated imagery to match against real in s...

The correlation filters for pattern recognition, have been extensively studied in the areas of automatic target recognition(ATR) and biometrics. Whereas the conventional correlation filters perform directly on image pixels, in this paper, we propose a novel method, called “feature correlation filter (FCF)”, by extending the concept of correlation filter to feature spaces. The FCF preserves the ...