The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents a method to detect small flooded areas from images which contain also vegetation zones. So, two classes are considered: flood class and vegetation. For the learning phase a supervised technique based on small patches is used. Based on efficiency analysis, the Histograms of Oriented Gradients on H colour channel and mean intensity on gray level are selected as discriminated features...
This paper proposes a convolutional neural network architecture for blood vessel segmentation in retinal images. The network structure is designed on 7 layers using MatConvNet (three convolutional layers, two pooling layers, one dropout layer and a Softmax layer). The input data, selected from the DRIVE database, of the neural network is preprocessed in Matlab on Green channel. The retinal image was...
In this paper, we develop an methodology and corresponding algorithms that segments regions of interest like vegetation and flood from aerial images. To this end different textural features are used, particularly second order type (extracted from co-occurrence matrix — Haralick features) and histogram of oriented gradients (HOG). These features are calculated from image patches and the obtained values...
The paper presents a method for accurate detection and localization of important regions from retinal images like: optic disc, macula, exudates and hemorrhages. To this end, the image is locally decomposed in sub-images (patches) and then it is processed based on the fusion of different information types: first order statistics, textural, fractal and spectral. Two multilayer processing networks are...
The paper presents a new methodology for the detection and accurate localization of the optic disc in retinal images. Different color channels are investigated and, as a result, LBP histogram on Hue channel is combined with the information of intensity level on Green channel. The proposed algorithm is applied on overlapped patches, having a corresponding dimension, extracted from the retinal images...
This paper extends some previous work on trajectory generation for UAV (Unmanned Aerial Vehicles) using differential flatness in combination with B-splines parametrization. The originality of this work resides in the geometrical interpretations of the B-splines properties and their use in generating feasible flat trajectories for nonlinear UAV dynamics while ensuring continuous constraint validation...
Traditional industrial systems have been designed to ne intrinsically safe by isolating their monitoring and control network. Considering the possible impact of a security attack, many plants today still choose to use this method to ensure maximum protection. At the same time, a separate trend observed in highly distributed applications like water management systems, is to centralize more local SCADA...
This paper addresses the practical aspects of basic design for prototyping a MAS that will manage the control functions of onshore oilfield automation as services. The technologies used in IT and Automation are more and more the same and Service Oriented Architectures and Cloud Computing have been adopted in process control world. Remarkable works present or debate architectures and technologies for...
This article discusses the new IEC61850 Standard for Substation Automation, considering its functionalities, requirements, and definitions. It provides an application-oriented approach through the capabilities that the new tools and Intelligent Electronic Devices (IEDs) allow. The work highlights the importance of modern IEDs, emphasizing the main characteristics that these components must possess...
This work proposes a texture classification algorithm using three elements of fractal analysis: fractal dimension, lacunarity and succolarity. Beside other papers, the interconnection of fractal elements is taken into account as a texture classification factor. The three fractal analysis elements are presented in the paper and were implemented using Matlab. Fractal dimension spectrum, mean of lacunarity...
This paper proposes an improved method for automated segmentation of images containing small flooded areas, in order to evaluate the material damage in rural zones. The solution consists on a hybrid wireless sensor network composed of two parts: the aerial mobile nodes (for surveillance and monitoring of flood affected areas) and the fixed nodes at the ground (for control, image processing and flood...
Wireless Sensor Networks (WSNs) comprising a large number of sensing nodes deployed within the area of interest, are able to measure, process and share specific parameters. Besides enabling effective area coverage, recent research has proven that unmanned aerial vehicles (UAVs) represent a viable addition to large area monitoring through remote sensing and data collecting functions. The proposed interlinking...
In this paper we propose a new method for the detection and evaluation of exudates in retinal images. In the learning phase we focus on selecting efficient features that can uniquely identify the exudates. In this process we develop a neural network for image processing. We then further extend and train the neural network to detect and evaluate the exudates. The efficiency of the proposed method is...
This paper develops a new method based on intelligent feature selection for aerial image segmentation. In order to select the best feature for segmentation we considered different regions of interest like floods and roads, taking into account information about color and texture. The features investigated derived from the inter-spectral co-occurrence matrices between the color channels RGB and HSV...
The paper presents a new method for detecting and localizing regions of interest (ROI) in retinal images. In the learning phase, the focus is on an efficient feature selection based on K-means clustering of feature values and on artificial neural networks (ANNs) for image processing and textural features computation. Finally, a voting scheme identifies the regions of interest. The experiments were...
The paper presents an efficient method for image segmentation based on inter-spectral information. Two classes of regions were considered: flooded and non-flooded. The images were captured by unmanned aerial vehicles (UAV), fix-winged type. Using features extracted from benchmark samples of each texture, flooded areas are automatically recognized from input test images. Our results show that the Haralick...
The paper presents a new method for the detection of exudates and hemorrhages in eye-fundus images using a voting scheme for the selection of efficient features. Also it was used a new algorithm for feature selection based on a statistical indicator of performance. The used features include statistical, textural and fractal characteristics of the corresponding areas in the eye-fundus images. A combination...
In this paper, we propose a novel methodology for the detection and the evaluation of flooded areas from different regions affected by this form of natural disaster. The proposed methodology considers various information from both RGB and HSV color representations and it is based on two phases (learning and segmentation). The main task is to determine the size of the flooded area from each analyzed...
Oil and Gas operations across the value chain are fraught with challenges in maximizing margins while mitigating risks of owning and operating critical infrastructure. The need for Integrated Operations is increasing and Industry 4.0 paradigm acts like a lighthouse. Holonic approach, Multi-Agent Systems and IEC 61499 may be used to address the required intelligence of petroleum production systems...
In the case of events like earthquakes and floods, for the disaster evaluation, an analysis of remote images is necessary. In this paper we propose a method for remote image classification based on texture analysis of small patches from global images taken by UAV. To this end a measure based on dissimilarity between feature signatures of the analyzed patch and prototype of classes is used. The proposed...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.