A reconfigurable computing architecture based on Field Programmable Gate Array (FPGA) technology is implemented for the Electrical Capacitance Tomography (ECT) system. The ECT system is used to image the multi-phase f...
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ISBN:
(纸本)9781509034741
A reconfigurable computing architecture based on Field Programmable Gate Array (FPGA) technology is implemented for the Electrical Capacitance Tomography (ECT) system. The ECT system is used to image the multi-phase flow when gas/liquid or solid/liquid phases occurs. In the ECT systems, an exhaustive computational image reconstruction algorithm has to vastly processed large amount of data. The software algorithms and hardware parameters are adjusted based on a Hardware software codesign process using commercially available tools. The hardware system consists of capacitive sensors, wireless nodes and FPGA module. Rr4wesults show that implementing the ECT image reconstruction algorithm on the FPGA platform achives fast performance and small design density.
For many imageprocessing workflows, including change detection and data fusion, an accurate and automated image-To-image registration is a critical precondition. Particularly registering images with different modalit...
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In surveillance systems a constant monitoring is required for high security purpose, however the videos or the images captured here can be degraded because of low illumination environment and foggy atmosphere. In this...
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In surveillance systems a constant monitoring is required for high security purpose, however the videos or the images captured here can be degraded because of low illumination environment and foggy atmosphere. In this paper we have developed a system that acquires images through motion detection and enhance the quality of image with illumination adjustment and haze removal algorithms in FPGA. The motion detection algorithm has been implemented in MATLAB r2013a whereas the acquired image has been processed in FPGA Virtex 6 ML605 evaluation board. The visual quality of the image cannot be judged merely by observing image but also by determining some parameters like PSNR, MSE etc. So on the basis of implementation results it has been observed that the illumination levels of the image has been adjusted and the haze has been removed to some extent and in addition to that the system requires less time for processing purpose.
Steganalysis is capable of identifying the carrier(s) which have information hidden in them in such a way that their very existence is concealed. In this paper we propose a classification system with neural networks w...
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ISBN:
(纸本)9781509010226
Steganalysis is capable of identifying the carrier(s) which have information hidden in them in such a way that their very existence is concealed. In this paper we propose a classification system with neural networks which reduces computational complexity through a pre-processing step (feature selection) performed by Bhattacharyya distance for image steganalysis. This approach is able to identify relevant features which are a subset of original features extracted from spatial as well as transform domain. It helps in overcoming the problem of "curse of dimensionalty" by removing redundant features by feature selection step before classifying the dataset. The experiments are performed on dataset obtained by four steganography algorithms outguess, steghide, PQ and nsF5 with two classifiers Support Vector Machine and Back Propagation neural networks. Classifier in combination with Bhattacharyya distance filter feature selection approach shows an improvement of 2-20% against total number of features.
The proceedings contain 50 papers. The topics discussed include: a rational multiparty information exchange model using extensive games;RSS-based secret key generation for indoor and outdoor WBANs using on-body sensor...
ISBN:
(纸本)9781509017775
The proceedings contain 50 papers. The topics discussed include: a rational multiparty information exchange model using extensive games;RSS-based secret key generation for indoor and outdoor WBANs using on-body sensor nodes;robust spectrum sensing algorithms under noise uncertainty;multicarrier modulation for HFe MANET in the Presence of communications;joint protection of a military formation using heterogeneous sensors in a mobile ad hoc network: concept and field tests;learning multi-channel power allocation against smart jammer in cognitive radio networks;and complex event processing for content-based text, image, and video retrieval.
Support Vector Machine (SVM) classifiers are widely used to analyse features extracted from brain MRI data to identify useful biomarkers of pathology in several disease conditions. They are trained to distinguish pati...
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Several major advances in Cell and Molecular Biology have been made possible by recent advances in livecell microscopy imaging. To support these efforts, automated image analysis methods such as cell segmentation and ...
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Content-Based image Retrieval (CBIR) aims to retrieve similar graphical objects from large databases based on their contents. CBIR requires definition of descriptors, algorithms that condense information from the obje...
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ISBN:
(纸本)9781509035687
Content-Based image Retrieval (CBIR) aims to retrieve similar graphical objects from large databases based on their contents. CBIR requires definition of descriptors, algorithms that condense information from the object in order to represent it usually as a real number or a vector in Rn. This article presents the Spectral Descriptor, a new descriptor designed for retrieving three-dimensional geometric objects applied to aid the diagnosis of Congestive Heart Failure (CHF). Our descriptor is based on techniques of compressive sensing and rewrites the coordinates of 3D objects vertices on a basis on which they have a sparse representation. Tests with surfaces reconstructed from heart MRI images, specifically from left ventricle, show that the descriptor has presented a good performance, reaching an average precision of approximately 85% for CHF and 71% for non-CHF cases, maintaining high levels of precision. Results also showed that the Spectral Descriptor can decrease the high dimensionality of features vectors in CBIR systems.
An instrument to improve the quality of life in large cities, helping to reduce the car traffic, is presented in this paper. It will result in a mobile guidance software that will help the drivers looking for a parkin...
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ISBN:
(纸本)9781509018574
An instrument to improve the quality of life in large cities, helping to reduce the car traffic, is presented in this paper. It will result in a mobile guidance software that will help the drivers looking for a parking place to find it efficiently. SmartPark relies on available parking information systems, as well as on new sensors or even on social data inputs. A fixed magnetic on-street sensor and a video processing smart camera have been developed and prototypes of both devices were tested. Their data is available through a cloud-based Internet of Things infrastructure and continuously updated every few seconds. Databases will be built over time enabling data mining methods to infer parking availability models over time which will be used, eventually, by the algorithms feeding the mobile application.
Feature selection, as a preprocessing step to machine learning, plays a pivotal role in removing irrelevant data, reducing dimensionality and improving performance evaluations. Recent years, sparse representation has ...
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