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Interest on palmprint biometrics has experimented a strong growth in the last decades due to its useful characteristics as uniqueness, permanence, reliability, user-friendliness, acceptability, non-intrusiveness, and low cost of the acquisition devices, which make it attractive for civil and commercial applications. Accordingly, a wide research has been developed in this field. Nevertheless, there...
The analysis of scientific data, specially in different kinds of cosmological studies, has to deal with the increment in data volume. These studies include the calculation of correlation functions such as the Two-point Three-Dimensional Correlation Function. To get the final estimator value for these functions, it is necessary to construct histograms for storing large number counts. Histograms are...
In this article the results of testing of numerical methods of solution of differential equations describing the systems with chaotic dynamics in MATLAB are discussed. The results of evaluation of the actual error, the global error and root-mean-square error of the numerical solution of the test differential equation system are discussed. The results of evaluation of the main radio technical parameters...
Privacy-preserving data publishing is an important problem which exists in research and has become increasingly vital in recent years. We come across situations where a data owner wishes to publish data without revealing private information. A known solution to this problem is differential privacy which is a research topic that implements noise injection using the Laplace distribution and building...
A deoxyribonucleic acid (DNA) microarray is a powerful tool that is widely used in genetics to monitor the expression levels of thousands of genes in parallel. Gridding, segmentation and intensity extraction is the process of gene expression. In the process of gene expression, gridding process information leading to dig their own DNA and provide coordinates for each point. Gridding can be implemented...
Skull stripping is an useful technique for segmenting the brain tissue which is used for analysis of neuroimaging data. Thus accurate segmentation of brain tissue by removal of non-brain tissues like skull, muscle/skin, and cerebrospinal fluid is an important task for diagnosis a disease and pre-planning for a surgery. In this paper we present a technique for segmenting the brain from skull in a synthetic...
The performance of pattern classifiers depends on the separability of the classes in the feature space — a property related to the quality of the descriptors — and the choice of informative training samples for user labeling — a procedure that usually requires active learning. This work is devoted to improve the quality of the descriptors when samples are superpixels from remote sensing images. We...
Several algorithms for polarimetric synthetic aperture radar (PolSAR) data indexing and classification were proposed in the state of the art literature. In particular, one of them computes powerful, compact feature descriptors composed of the first three logarithmic cumulants of the BiQuaternion Fractional Fourier Transform (BiQFrFT) coefficients of PolSAR patches. Since the BiQFrFT of each patch...
Feature extraction is at the core of satellite scene classification task. In this paper, we propose a fast binary coding (FBC) method to effectively generate the global discriminative feature representation of image scenes. Equipped with unsupervised feature learning technique, we first learn a set of optimal “filters” from large quantities of randomly sampled image patches, and then we obtain feature...
Collecting data at regular time nowadays is ubiquitous. The most widely used type of data that is being collected and analyzed is financial data and sensor readings. Various businesses have realized that financial time series analysis is a powerful analytical tool that can lead to competitive advantages. Likewise, sensor networks generate time series and if they are properly analyzed can give a better...
Spatial information describes the relative spatial position of an object in a video. Such information may aid several video analysis tasks such as object, scene, event and activity recognition. This paper studies the effect of spatial information on video activity recognition. The paper firstly performs activity recognition on KTH and Weizmann videos using Hidden Markov Model and k-Nearest Neighbour...
The Spatial Pyramid Matching approach has become very popular to model images as sets of local bag-of-words. The image comparison is then done region-by-region with an intersection kernel. Despite its success, this model presents some limitations: the grid partitioning is predefined and identical for all images and the matching is sensitive to intra- and inter-class variations. In this paper, we propose...
In this paper we present a novel way of applying Zernike moments for image matching. Zernike moments are obtained from projecting image information under a circumscribed circle to Zernike basis function. However, the problem is that the power of discrimination may be reduced because hand images include lots of overlapped information due to their shape characteristic. On the other hand, in the pose...
In this paper we present a comparison between various statistical descriptors and analyze their goodness in classifying textural images. The chosen statistical descriptors have been proposed by Tamura, Battiato and Haralick. In this work we also test a combination of the three descriptors for texture analysis. The databases used in our study are the well-known Brodatz's album and DDSM (Heath et al...
In surveillance and scene awareness applications using power-constrained or battery-powered equipment, performance characteristics of processing hardware must be considered. We describe a novel framework for moving processing platform selection from a single design-time choice to a continuous run-time one, greatly increasing flexibility and responsiveness. Using Histogram of Oriented Gradients (HOG)...
Many computer vision applications adopting consumer depth cameras have recently received much attention due to the availability at low prices and the potential benefits to provide more useful information, which can result in a higher accuracy (e.g., for object recognition). In this work, to address the problem of drinking activity recognition in vision-based Ambient Assisted Living by using depth...
Most of the stereo-matching algorithms nowadays need high accuracy, especially for objects at large distances. Lots of approaches are able to provide good results at low costs, but at large distances (small disparities) suffer from the so called “pixellocking effect” i.e. an uneven sub-pixel disparity distribution. In order to compensate this effect, developing sub-pixel interpolation functions can...
This paper proposes a feature-based technique to detect pedestrians and recognize vehicles within thermal images that have been captured during nighttime. The proposed technique applies the support vector machine (SVM) classifier on CENsus Transformed histogRam Oriented Gradient (CENTROG) features in order to classify and detect humans and/or vehicles. Although thermal images suffer from low image...
This work focuses on automatic prediction of the writer's biometrics including gender, handedness and age information. The proposed prediction system is based on the use of Histogram of Oriented Gradients (HOG), which aims to extract gradient directions from the handwritten text. The prediction task is achieved using SVM classifier. Experiments performed on IAM and KHATT datasets, reveal promising...
Human-action recognition through local spatio-temporal features have been widely applied because of their simplicity and its reasonable computational complexity. The most common method to represent such features is the well-known Bag-of-Words approach, which turns a Multiple-Instance Learning problem into a supervised learning one, which can be addressed by a standard classifier. In this paper, a...
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