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In many circumstances the limitation for use of video cameras is energy. The energy needed for compression and transmission of video is substantial, and is linear with the number of transmitted frames. Time-lapse photography, a drastic reduction of transmitted frame rate, is an obvious solution, say by transmitting one frame every several minutes. The temporal resolution of the video is lost. Can...
We previously proposed the artificial fiber (AF) patterns in order to be able to hide information in printed documents. AF pattern uses the features of the medium (e.g., paper). It has features of rotational invariance, low visibility of the hidden information. But it still suffered extraction threshold instability when using a camera to extract the information. This problem has now been overcome...
Currently, most datasets from real-world problems contain low-quality data. In particular, within soft computing and data mining areas, the research and development of techniques that can deal with this type of data has been increased recently. In order to facilitate the design of experiments in this field and with these data, an experimenter environment in NIP imperfection processor software tool...
Detecting changes in data streams is an important area of research in many applications. The challenging issue is to know how to monitor, update and diagnose these changes so that the accuracy of the learner will be improved whatever the nature of the encountered drifts. In this paper a new error distance based approach for drift detection and monitoring, namely EDIST, is proposed. In EDIST, a difference...
According to the features of SAR image, a new algorithm for image registration based on straight lines is proposed. It is divided to four steps: firstly, compute the attribute parameters of straight lines according to the angles between the line and its neighbor lines. Then, design proper similarity measure function to compute the similarity between lines and find the cursory match result. Thirdly,...
Independent Component Analysis (ICA) algorithms taking advantage of the potential non-circular property of complex signals have been recently derived and shown to lead to improved performances. We investigate the performance of three ICA approaches to extract a weak co-channel interfering communications signal from a television broadcast signal over varied interference-to-noise ratios: complex maximization...
In speech processing systems, the performance of the Voice Activity Detector (VAD) is a bottleneck to the whole system. Traditional VADs are solely based on acoustic features. Additional modality in form of visual information is used to make robust VADs. In this paper, we propose a multimodal VAD based on decision fusion between two modalities. Visual VAD (VVAD) decision vectors are interpolated so...
This paper proposes a novel approach that allows region-based active contour energy to be re-expressed combining local and global information. The basic idea of this technique consists in extracting image statistics locally from the heterogeneous region (foreground or background) and globally from the other region at each point along the curve. By exploiting benefits of both local-based and global-based...
Traditional rough set of noise data, the lack of adaptability, lack of flexibility or robustness, for the engineering data can not distinguish between equivalence classes of edge region of overlap with the collection, resulting in loss of many valuable engineering information. Strong noise in the actual engineering data over-fitting due to reduced ability to distinguish the object, its limitations...
In this article we present a new approach to extract points that belongs to several ellipses or circles presented on a same image and with the presence of outliers. Each geometric form is extracted by means of a robust fitting, that is a nonlinear optimization problem, solved with two different heuristics: differential evolution and RANSAC. Once the geometric form is fitted, its points are extracted...
In this paper we address the topic of feature extraction in 3D point cloud data for object recognition and pose identification. We present a novel interest keypoint extraction method that operates on range images generated from arbitrary 3D point clouds, which explicitly considers the borders of the objects identified by transitions from foreground to background. We furthermore present a feature descriptor...
This paper proposes a robust blind watermarking scheme for 2D-vector data used in Geographical Information Systems (GIS). The proposed method embeds two types of watermarks that complement each other into the vector data. It preserves the fidelity of the vector data using an intersection test. Simulation results show that our method is resistant to common attacks such as translations, scaling, rotation,...
Several non-supervised machine learning methods have been used in the analysis of gene expression data obtained from microarray experiments. Recently, biclustering, a non-supervised approach that performs simultaneous clustering on the row and column dimensions of the data matrix, has been shown to be remarkably effective in a variety of applications. The discovery of biclusters, which denote groups...
Tracking concept drifts in data streams has recently become a hot topic in data mining. Most of the existing work is built on a single-window-based mechanism to detect concept drifts. Due to the inherent limitation of the single-window-based mechanism, it is a challenge to handle different types of drifts. Motivated by this, a new classification algorithm based on a double-window mechanism for handling...
In an earlier work, we proposed Density Based Fuzzy C Means algorithm to identify noise and create clusters by changing Fuzzy C-Means (FCM) membership as well as objective functions. The constraint in changing membership in that algorithm produced a few unrealistic membership function values. In this paper, we propose Density Oriented Fuzzy C-Means (DOFCM) model that can detect efficient clusters...
Digital watermark technology of GIS vector data consists of designing the digital watermark algorithm and evaluating the digital watermark algorithm performance, also, robustness is a most important evaluation indicator of the digital watermark algorithm performance, therefore, this article focuses on evaluating the robustness of digital watermark algorithm of GIS vector data.
This paper studied the robustness of ARX model by varying the noise sequence adapted to the output of a heating process. The ARX model is fitted from output data which is obtained from a pilot plant of essential oil extraction by applying steam distillation technique. The plant is supplied by 1.5kW power delivered to the heating element which then is converted into PRBS signal as input and produced...
This paper presents an extended Kalman filter for discrete-time nonlinear systems subject to uncertainties. The proposed filter considers that the linearization of the nonlinear functions are unknown, but within a known set. The nonlinear functions are assumed to belong to a conic region. This condition is characterized as a Lipschitz condition on the system state, control signal and the noise residuals...
We propose a new family of classification algorithms in the spirit of support vector machines, that builds in non-conservative protection to noise and controls overfitting. Our formulation is based on a softer version of robust optimization called comprehensive robustness. We show that this formulation is equivalent to regularization by any arbitrary convex regularizer. We explain how the connection...
This paper presents a novel statistical method for background subtraction aimed at robustness with regards to common disturbance factors such as sudden illumination changes, variations of the camera parameters, noise. The proposed approach relies on a novel non-linear parametric model for the local effect of disturbance factors on a neighbourhood of pixel intensities. Assuming additive Gaussian noise,...
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