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This paper investigates the influence of the signal to noise ratio (SNR) and the type of a noise on the performance of two adaptive novelty detection methods. The evaluated methods are Learning Entropy (LE) and Error and Learning Based Novelty Detection (ELBND). The methods are compared in empirical way in classification framework. A classification based only on the error of the adaptive model was...
Change detection in multitemporal hyperspectral images (HSI) can be regarded as a classification task, consisting of two steps: change feature extraction and identification. To extract clean change features from heavily corrupted spectral change vectors (SCV) of multitemporal HSI, this paper proposes a novel spectrally-spatially regularized low-rank and sparse decomposition model (LRSDSS). It exploits...
There is a current trend towards wearable electrocardiogram (ECG) measurement systems, which enables measurement while the subject performs their normal activities of daily living (e.g., walking, driving, eating). This type of measurement is susceptible to higher levels of contaminants, compared to bedside measurements, due to subject movement and a measurement environment that is not well-controlled...
Partial discharge (PD) can be used to predict insulation failures in power transformers. Accurate detection of particular PD types has a significant role in anticipating forthcoming outages. However, the noise encountered with PD measurements negatively affects the detection accuracy. In this paper, we propose a robust PD detection technique that is immune to noise through efficient frequency domain-based...
Texture images of limited size can be insufficient for statistical learning to perform the task of image retrieval. This paper proposes a hypothesis that the utilization of synthesized texture and noise addition can improve texture analysis with spatial statistics. Rationales for this hypothesis are that texture synthesis allows the enlargement of an image size for better description of its spatial...
Electromyography (EMG) signals have been extensively used as a control signal in robotics, rehabilitation and health care. In this paper, cost effective design of prosthetic hand using EMG control is presented. Signal amplification and filtering is the primary step in surface EMG signal processing and application systems. Quality of the acquired EMG signal depends on the amplifiers and filters employed...
Performance of image mosaicing depends on overlap between the images to be joined and the percentage of noise present. An algorithm is used for joining images based on image matching by comparing the descriptors for different images. This paper is concerned with the analysis of effect of variations in noise and degree of relative overlap on the algorithm and obtaining their limits. Speeded Up Robust...
Chirplet transform performance to identify low-frequency blue whale calls is tested with simulations and observations from North-West Atlantic. The three different calls are simulated using linear or quadratic frequency sweeping chirps and a hanning window. The performance of Chirplet transform to accurately estimate the chirp parameters with or without noise is first assessed. Then the performance...
To segment multi-spectral remote sensor images, feature extraction and object classification is an essential step that performs region-based segmentation instead of a pixel-based segmentation. Spectral based segmentation methods like K-Means, Mean-shift segmentation fail to extract optimal regions from multi-spectral images. In high-resolution multi-spectral images, segmentation main aim is to divide...
An automatic, text-independent speaker verification (SV) system is proposed using Line Spectral Frequency (LSF) features. The state-of-the-art Gaussian Mixture Model with Universal Background Model (GMM-UBM) framework is used for speaker modeling and verification. A score-level fusion based technique is employed in order to extract complementary information from static and dynamic LSF features and...
In this paper, we present a scene recognition framework, which could process the images and recognize the scene in the images. We demonstrate and evaluate the performance of our system on a dataset of Oxford typical landmarks. In this paper, we put forward a novel method of local k-meriod for building a vocabulary and introduce a novel quantization method of soft-assignment based on the Gaussian mixture...
To improve the quality of video surveillance in outdoor and automatic acquire of the weather situations, a method to recognize weather phenomenon based on outdoor images is presented. There are three features of our method: firstly, the features, such as the power spectrum slope, contrast, noise and saturation and so on are extracted, after analysing the effect of weather situations on image; secondly,...
In this paper we present a framework for the estimation of the pose of an object in 3D space: from the detection and subsequent recognition from a 3D point-cloud, to tracking in the 2D camera plane. The detection process proposes a way to remove redundant features, which leads to significant computational savings without affecting identification performance. The tracking process introduces a method...
A problem of detecting textural areas in images corrupted by noise is considered. Detection is based on joint use of several local parameters calculated in scanning windows (blocks) of different size. Trained support vector machine (SVM) classifier is used for combining local parameters. Factors that influence detector performance are analyzed. It is shown that detector performance can be improved...
Trajectories obtained from low level tracking algorithm provide an opportunity for us to analyze meaningful behaviors and monitor adverse or malicious events. How to abstract meaningful features from the raw data of trajectories is a challenge due to the high dimensionality and noise. In this paper, a novel approach, stacked denoising autoencoder(SDA) is applied to address this problem. This method...
In this letter, a simple, yet very powerful local descriptor called local pattern descriptor (LPD) is proposed for synthetic aperture radar (SAR) images classification. The descriptor aims at exploiting the underlying properties of SAR image texture. Specifically, LPD consists of two parts: image quantization and statistical features extraction. The method of image quantization is based on recent...
In this paper we concentrate our efforts on the analysis of the facial landmarks dynamics as being a relevant method to access the subject's emotion. Given the person's facial landmarks we describe their trajectory with respect to the neutral pose and out of this trajectory we extract relevant features that are subsequently entered into a classification system for the actual recognition of emotion...
In order to achieve vial bottle mouth defect detection, this paper proposes a vial bottle mouth defect detection scheme based on machine vision. The scheme is mainly using machine vision software HALCON to study. Firstly, the noise in the bottle mouth image is removed by filtering. Secondly, separating target and background by threshold segmentation. Then, extracting the edges through the edge detection,...
this paper presents a new approach to extract image features for texture classification. The extracted features are obtained by a dominant-completed modeling of the traditional local binary pattern (LBP) operator, which is robust to image rotation, grey scale changing and insensitive to noise and histogram equalization. The main idea of this texture classification approach is that a dominant center...
Information to be exchanged between two parties needs compression for achieving its efficient transmission. Encoded information gets distorted during its transmission over a channel due to noise. For monitoring and analysis of such noisy traffic of an adversary over communication networks, it is required to find the type of information, whether it is text or speech, then to restore it for further...
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