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SAR image time series analysis in vegetation classification using global and local information based linear discriminant analysis

SAR image time series analysis in vegetation classification ...

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IEEE signal processing and Communications applications (SIU)

作者： Ufuk Sakarya Caner Demirpolat TÜBITAK UZAY ODTÜ Ankara

ISBN: (纸本)9781509064953

Vegetation classification using SAR images is one of the research topics in remote sensing. In this paper, SAR image time series analysis in vegetation classification using global and local information based linear discriminant analysis is presented. It is experimentally demonstrated that the use of local pattern information in addition to global pattern information has increased both accuracy and time performance in vegetation classification using time-series TerraSAR-x images.

关键词： Synthetic aperture radar Remote sensing Principal component analysis Linear discriminant analysis Time series analysis Vegetation mapping Pattern recognition

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Use of patient specific 3D printed neurovascular phantoms to evaluate the clinical utility of a high resolution x-ray imager

Use of patient specific 3D printed neurovascular phantoms to...

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SPIE Biomedical applications in Molecular, Structural, and Functional Imaging conference

作者： Nagesh, S. V. Setlur Russ, M. Ionita, C. N. Bednarek, D. Rudin, S. Univ Buffalo Toshiba Stroke & Vasc Res Ctr Buffalo NY 14228 USA

ISBN: (纸本)9781510607194;9781510607200

Modern 3D printing technology can fabricate vascular phantoms based on an actual human patient with a high degree of precision facilitating a realistic simulation environment for an intervention. We present two experimental setups using 3D printed patient-specific neurovasculature to simulate different disease anatomies. To simulate the human neurovasculature in the Circle of Willis, patient-based phantoms with aneurysms were 3D printed using a Objet Eden 260V printer. Anthropomorphic head phantoms and a human skull combined with acrylic plates simulated human head bone anatomy and x-ray attenuation. For dynamic studies the 3D printed phantom was connected to a pulsatile flow loop with the anthropomorphic phantom underneath. By combining different 3D printed phantoms and the anthropomorphic phantoms, different patient pathologies can be simulated. For static studies a 3D printed neurovascular phantom was embedded inside a human skull and used as a positional reference for treatment devices such as stents. To simulate tissue attenuation acrylic layers were added. Different combinations can simulate different patient treatment procedures. The Complementary-Metal-Oxide-Semiconductor (CMOS) based High Resolution Fluoroscope (HRF) with 75 mu m pixels offers an advantage over the state-of-the-art 200 mu m pixel Flat Panel Detector (FPD) due to higher Nyquist frequency and better DQE performance. Whether this advantage is clinically useful during an actual clinical neurovascular intervention can be addressed by qualitatively evaluating images from a cohort of various cases performed using both detectors. The above-mentioned method can offer a realistic substitute for an actual clinical procedure. Also a large cohort of cases can be generated and used for a HRF clinical utility determination study.

关键词： Sensors 3D modeling x-rays signal attenuation 3D printing Arteries Head Computer simulations Skull image resolution 3D image processing Bone Printing x-ray imaging

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Exploration of TMR fault masking with persistent threads on tegra GPU SoCs

Exploration of TMR fault masking with persistent threads on ...

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2017 IEEE Aerospace conference, AERO 2017

作者： Milluzzi, Andrew George, Alan NSF CHREC Center ECE Dept. University of Florida Benton Hall GainesvilleFL32611 United States NSF CHREC Center ECE Dept. University of Pittsburgh Benedum Hall PittsburghPA1526 United States

ISBN: (纸本)9781509016136

Low-power, high-performance, System-on-Chip (SoC) devices, such as the NVIDIA Tegra K1 and Tegra x1, have many potential uses in aerospace applications. Fusing ARM CPUs and a large GPU, Tegra SoCs are well suited for image and signal processing. However, fault masking and tolerance on GPUs is relatively unexplored for harsh environments. With hundreds of GPU cores, a complex caching structure, and a custom task scheduler, Tegra SoCs are vulnerable to a wide range of single-event upsets (SEUs). Triple-modular redundancy (TMR) provides a strong basis for fault masking on a wide range of devices. GPUs pose a unique challenge to a typical TMR implementation. NVIDIA's scheduler assigns tasks based on available resources, but the scheduling process is not publicly documented. As a result, a malfunctioning core could be assigned the same block of code in each TMR module. In this case, a fault could go undetected, impacting the resulting data with an error. Likewise, an upset in the scheduler or cache could have an adverse impact on data integrity. In order to mask and mitigate upsets in GPUs, we propose and investigate a new method that features persistent threading and CUDA Streams with TMR. A persistent thread is a new approach to GPU programming where a kernel's threads run indefinitely. CUDA Streams enable multiple kernels to run concurrently on a single GPU. Combining these two programming paradigms, we remove the vulnerability of scheduler faults, and ensure that each iteration is executed concurrently on different cores, with each instance having its own copy of the data. We evaluate our method with an experiment that uses a Sobel filter applied to a 640×480 image on an NVIDIA Tegra x1. In order to inject faults to verify our method, a separate task corrupts a memory location. Using this simple injector, we are able to simulate an upset in a GPU core or memory location. From this experiment, our results confirm that using persistent threading and CUDA Streams with T

关键词： Graphics processing unit

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x-ray Computed Tomography simultaneous image reconstruction and contour detection using a hierarchical Markovian model

X-ray Computed Tomography simultaneous image reconstruction ...

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IEEE International conference on Acoustics, Speech and signal processing

作者： Li Wang Ali Mohammad-Djafari Nicolas Gac Laboratoire des Signaux et Systeme CentraleSupelec Gif sur Yvette France

ISBN: (纸本)9781509041183

The 3D x-ray Computed Tomography (CT) is used in many domains. In medical imaging and industrial Non Destructive Testing (NDT) applications, this technique becomes of great interest. In these applications, very often, we need not only to reconstruct the image, but also to detect the contours between the homogeneous regions of the piecewise continuous image. Generally, contours are obtained by a post processing from the reconstructed image. In this paper, we propose a method to estimate image and contour simultaneously. For this we use the Bayesian approach with a prior model in which the relationship between the image and its contour is considered by using a hierarchical Markovian model, and use a sparsity enforcing prior model for the contours. This proposed method can be used for reconstructions when the image is piecewise continuous. The simulation results are compared with some state of the art methods, and they show the efficiency of simultaneously reconstructing and edge detecting by using proposed method.

关键词： Computed Tomography Non Destructive Testing Simultaneous reconstruction and contour detection Markovian Model Generalized Student-t distribution Nondestructive Testing x-Ray Computed Tomography contour imagery (Psychotherapy) images contour detection image reconstruction state of the art Outlines image Piecewise continuous Bayes methods

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Efficient BSIF-based Near-Infrared Iris Recognition 6

Efficient BSIF-based Near-Infrared Iris Recognition

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6th International conference on image processing Theory, Tools and applications (IPTA)

作者： Rathgeb, C. Struck, F. Busch, C. Hsch Darmstadt Da Sec Biometr & Internet Secur Res Grp Darmstadt Germany

ISBN: (纸本)9781467389105

Binarized statistical image features (BSIF) represents a general purpose texture descriptor originally designed for texture description and classification, such as local binary patterns (LBP) or local phase quantisation (LPQ). Recently, BSIF has extensively been applied for the purpose of biometric recognition, for instance based on face or palmprint images. While recognition accuracy reported for different biometric characteristics indicates its applicability to iris recognition, up till now BSIF has primarily been employed for iris spoofing detection in particular, fake contact lens detection. In this work we present an adaptation of BSIF for near-infrared iris recognition. In accordance with generic iris recognition schemes, a specific alignment procedure is introduced in order to achieve robustness against head tilts. Further, we propose a binarization method for BSIF-based feature histograms, to obtain a compact feature representation, which allows for a rapid comparison. On the CASIAv4-Interval iris database the proposed system achieves competitive biometric performance obtaining EERs below 0.6%, compared to traditional schemes based on Log-Gabor and quadratic spline wavelets revealing EERs of approximately 0.4%. Moreover, we show that BSIF-based feature vectors complement those extracted by traditional systems, yielding a significant performance gain in a multialgorithm fusion scenario resulting in an EER below 0.2%, which further underlines the usefulness of the presented approach.

关键词： Biometrics iris recognition binarized statistical image features biometric fusion

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Distance independent weight estimation of eggs from images using artificial neural networks

Distance independent weight estimation of eggs from images u...

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IEEE signal processing and Communications applications (SIU)

作者： Ünsal Burak Şalvarci Umut Engin Ayten Yıldız Teknik Üniversitesi Elektronik ve Haberleşme Mühendisliği Bölümü İstanbul Türkiye

Accurately and fast detection of weight of objects has an important place for lots of academic and industrial application at the present time. In this work, it was aimed to estimate weight of eggs in a distance independent manner using image processing and artificial neural networks (ANN). The constituted system consists of a camera, artificial lighting system, reflector and reference image. Object weight was estimated by processing the acquired image. Feed forward multilayer perceptron (MLP) was preferred as artificial neural network. 250 samples which consist of 4 different brands and 4 different classes (x-large, large, medium, and small) were used for testing and training the system. It was tried to be obtained optimum system by using different feature vectors, different images and different artificial neural network parameters. As accurate classification rate was %47 according to defined by Turkish food codex egg communique and classification values write on the egg cartoon, this rate was increased to %90.5 as a result of this work. All processes were realized by using MATLAB program and toolboxes.

关键词： MATLAB Artificial neural networks image processing Estimation Cameras Multilayer perceptrons Nanoelectromechanical systems

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Ultrasonic Damage Imaging of Structural Components with Bulk and Guided Waves using Match Coefficients

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SPIE conference on Health Monitoring of Structural and Biological Systems

作者： Sternini, S. Quattrocchi, A. Montanini, R. di Scalea, F. Lanza Univ Calif San Diego Dept Struct Engn NDE SHM Lab 9500 Gilman Dr La Jolla CA 92093 USA Univ Messina Dipartimento Ingn I-98158 Messina Italy

ISBN: (数字)9781510608269

ISBN: (纸本)9781510608252;9781510608269

Damage imaging of structural components in the field of Non Destructive Evaluations (NDE) and Structural Health Monitoring (SHM) using ultrasonic waves is usually performed by conventional imaging techniques, such as Delay-And-Sum (DAS), by back-propagating the recorded waveforms to identify locations and size of defects and damages. This technique results in sidelobes and artifacts that worsen the accuracy of the damage identification. Here we propose a novel imaging approach that derives from the well-known technique of Matched Field processing (MFP), often used in underwater acoustics and seismology. In MFP, the source or damage is located by a matching procedure between measurements ("data vector") and expected responses ("replica vectors") computed for each point of the imaging volume. In this work, we apply this matching approach only to selected features extracted from the recorded waveforms. These features, for example time-of-flights or amplitudes, will be selected for multiple modes of propagation of the ultrasonic waves (longitudinal and shear in bulk waves, multiple guided modes in waveguides). By considering multiple features and multiple wave modes, it is possible to increase the performance of this matching procedure, which can be possibly further improved by also combining different signal frequencies and excitation sources in analogy with biomedical ultrasonic imaging. A correlation metric showing high computational efficiency in the image reconstruction process will be tested as matching coefficient. applications of this imaging approach to a metallic plate with holes and simulated defects will be shown.

关键词： Synthetic Aperture Focus Ultrasonic Imaging Matched Field processing Structural Health Monitoring

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The reliability and accuracy of estimating heart-rates from RGB video recorded on a consumer grade camera 3

The reliability and accuracy of estimating heart-rates from ...

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conference on Optics and Biophotonics in Low-Resource Settings III

作者： Eaton, Adam Vincely, Vinoin Kurt, Paige Lloyd Hugenberg Vishwanath, Karthik Miami Univ Dept Phys Oxford OH 45056 USA Miami Univ Dept Psychol Oxford OH 45056 USA

ISBN: (数字)9781510605527

ISBN: (纸本)9781510605510;9781510605527

Video Photoplethysmography (VPPG) is a numerical technique to process standard RGB video data of exposed human skin and extracting the heart-rate (HR) from the skin areas. Being a non-contact technique, VPPG has the potential to provide estimates of subject's heart-rate, respiratory rate, and even the heart rate variability of human subjects with potential applications ranging from infant monitors, remote healthcare and psychological experiments, particularly given the non-contact and sensor-free nature of the technique. Though several previous studies have reported successful correlations in HR obtained using VPPG algorithms to HR measured using the gold-standard electrocardiograph, others have reported that these correlations are dependent on controlling for duration of the video-data analyzed, subject motion, and ambient lighting. Here, we investigate the ability of two commonly used VPPG-algorithms in extraction of human heart-rates under three different laboratory conditions. We compare the VPPG HR values extracted across these three sets of experiments to the gold-standard values acquired by using an electrocardiogram or a commercially available pulse-oximeter. The two VPPG-algorithms were applied with and without KLT-facial feature tracking and detection algorithms from the Computer Vision MATLAB (R) toolbox. Results indicate that VPPG based numerical approaches have the ability to provide robust estimates of subject HR values and are relatively insensitive to the devices used to record the video data. However, they are highly sensitive to conditions of video acquisition including subject motion, the location, size and averaging techniques applied to regions-of-interest as well as to the number of video frames used for data processing.

关键词： video photoplethysmography cardiovascular biomedical imaging image and signal processing

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A novel contextual speckle reduction method of PolSAR images: Evaluation of speckle reduction effects on sea ice classification

A novel contextual speckle reduction method of PolSAR images...

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Imaging and Geospatial Technology Forum 2017, IGTF 2017

作者： Mahdianpari, M. Salehi, B. Mohammadimanesh, F. Department of Electrical Engineering C-CORE Memorial University of Newfoundland Captain Robert A. Bartlett Building Morrissey Road St. John'sNLA1B3X5 Canada

Polarimetric Synthetic Aperture Radar (PolSAR) sensors can transmit and receive electromagnetic waves in different polarization states. As a result, PolSAR images are complex multi-dimensional data which can be extensively applied in sea ice monitoring and classification. The discrimination capability of PolSAR data makes them a unique source of information with a significant contribution to make in tackling problems concerning environmental applications, especially in the Arctic regions. The increasing temperature of the Earth due to climate change, combined with the degradation of ice thickness in the Arctic region increases the navigation of shipping routes more than ever before. Thus, oil and gas resources at high latitudes are more accessible, which will increase economic activities in the Arctic. Therefore, sea ice monitoring is one of the most important applications of remote sensing tools, since it is time and cost efficient in comparison with extensive field campaigns. Speckle reduction is one of the most important pre-processing steps in Polarimetric Synthetic Aperture Radar (PolSAR) image processing. This paper demonstrated the importance of the de-speckling method for sea ice classification using PolSAR image. A novel contextual speckle reduction method was proposed based on the integration of a Markovian energy function as a contextual analysis, and the Gaussian model as a pixel-wise analysis which maintained the mean value of original data in the homogenous areas and preserved the edges of features in the heterogeneous regions. Our proposed method is applied to a full polarimetric L-band dataset, ALOS-1 PALSAR acquired from Baffin Bay. The efficiency of the proposed method was compared with other well-known de-speckling methods, such as the Kuan method, the enhanced Lee method, and the Nonlocal Means and Refined Lee method. Different de-speckling indices, including the Mean Square Error (MSE), the signal to Noise Ratio (SNR), the Edge Saving Index (ESI

关键词： signal to noise ratio

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Vessel segmentation in angiography images with multi-scale filters

Vessel segmentation in angiography images with multi-scale f...

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IEEE signal processing and Communications applications (SIU)

作者： Mehmet Emin Tenekeci Hüseyin Pehlivan Abdülkadir GümüŞçü Kerim Karadağ Bilgisayar Mühendisliği Bölümü Harran Üniversitesi Şanlıurfa Türkiye Bilgisayar Mühendisliği Bölümü Karadeniz Teknik Üniversitesi Trabzon Türkiye Elektrik ve Elektronik Mühendisliği Bölümü Harran Üniversitesi Şanlıurfa Türkiye

Analysis of coronary angiography is very important for the diagnosis and treatment of heart diseases. The quality of the image is very low due to lack of usage of the x-ray and injected material, which are harmful to human health. For accurate segmentation and analysis the images need to be enhancement. In this study, a Gabor and 2d comparison filter was used to enhance the images and to highlight the vessel structures. It calculates the responses of different size and directional filters in both filters used. The improved images were segmented by P-Tile and Otsu thresholding methods and their performance was compared. The segmentation was performed on 5 different angiograms. The Gabor filter and the P-Tile thresholding method were found to be more successful with accuracy rate of mean all experiment %90,86 and maxium 92.4%.

关键词： Gabor filters image segmentation Angiography Filter banks x-ray imaging

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