Search results for: spherical images

Authors: Moung Young Lee, Chul Gyu Song

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Photoacoustic imaging is the imaging technology that combines the optical imaging and ultrasound. This provides the high contrast and resolution due to optical imaging and ultrasound imaging, respectively. We developed the real-time photoacoustic tomography (PAT) system using linear-ultrasound transducer and digital acquisition (DAQ) board. There are two types of algorithm for reconstructing the photoacoustic signal. One is back-projection algorithm, the other is FFT algorithm. Especially, we used the non-uniform FFT algorithm. To evaluate the performance of our system and algorithms, we monitored two wires that stands at interval of 2.89 mm and 0.87 mm. Then, we compared the images reconstructed by algorithms. Finally, we monitored the two hairs crossed and compared between these algorithms.

Keywords: back-projection, image comparison, non-uniform FFT, photoacoustic tomography

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Authors: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

Procedia PDF Downloads 130

Authors: Mehmet Doğan, Mahir Alkan, Yasemin Turhan, Zürriye Gündüz, Pinar Beyli, Serap Doğan

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Advances and new discoveries in the field of the material science on the basis of technological developments have played an important role. Today, material science is branched the lower branches such as metals, nonmetals, chemicals, polymers. The polymeric nano composites have found a wide application field as one of the most important among these groups. Many polymers used in the different fields of the industry have been desired to improve the thermal stability. One of the ways to improve this property of the polymers is to form the nano composite products of them using different fillers. There are many using area of boron compounds and is increasing day by day. In order to the further increasing of the variety of using area of boron compounds and industrial importance, it is necessary to synthesis of nano-products and to find yourself new application areas of these products. In this study, PMMA/boronoxide nano composites were synthesized using solution intercalation, polymerization and melting methods; and PAA/boronoxide nano composites using solution intercalation method. Furthermore, rheological properties of nano composites synthesed according to melting method were also studied. Nano composites were characterized by XRD, FTIR-ATR, DTA/TG, BET, SEM, and TEM instruments. The effects of filler material amount, solvent types and mediating reagent on the thermal stability of polymers were investigated. In addition, the rheological properties of PMMA/boronoxide nano composites synthesized by melting method were investigated using High Pressure Capillary Rheometer. XRD analysis showed that boronoxide was dispersed in polymer matrix; FTIR-ATR that there were interactions with boronoxide between PAA and PMMA; and TEM that boronoxide particles had spherical structure, and dispersed in nano sized dimension in polymer matrix; the thermal stability of polymers was increased with the adding of boronoxide in polymer matrix; the decomposition mechanism of PAA was changed. From rheological measurements, it was found that PMMA and PMMA/boronoxide nano composites exhibited non-Newtonian, pseudo-plastic, shear thinning behavior under all experimental conditions.

Keywords: boronoxide, polymer, nanocomposite, rheology, characterization

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Authors: João Cepeda

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In crafting their way between theory and practice, authors and artists seem to be always immersed in a never-ending process of relating epochs, objects, and images. Endless ‘affinities’ emerge from a somewhat unexplainable (and intimate) magnetic relation. It is through this ‘warburgian’ assessment that two of the most prominent twentieth-century modern architects from Japan and Portugal are put into perspective, focusing on their paths and thinking-practice, and on the research of their personal and professional archives. Moreover, this research especially aims its focus at essaying specifically on the possible ‘affinities’ between two of their most renowned architectural projects: the Kenzo Tange’s (demolished) Villa Seijo project in Tokyo (Japan) and Fernando Távora’s Tennis Pavilion design in Matosinhos (Portugal), respectively, side-by-side – through in-depth fieldwork in the sites, bibliographical and archival research, (unprecedented) material analysis, and final critical consideration.

Keywords: Tange, Távora, architecture, affinities

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Authors: Hatam H. Ali, Mohd Shahrizal Sunar, Hoshang Kolivand, Mohd Azhar Bin M. Arsad

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Rendering light shafts is one of the important topics in computer gaming and interactive applications. The methods and models that are used to generate light shafts play crucial role to make a scene more realistic in computer graphics. This article discusses the image-based shadows and geometric-based shadows that contribute in generating volumetric shadows and light shafts, depending on ray tracing, radiosity, and ray marching technique. The main aim of this study is to provide researchers with background on a progress of light scattering methods so as to make it available for them to determine the technique best suited to their goals. It is also hoped that our classification helps researchers find solutions to the shortcomings of each method.

Keywords: shaft of lights, realistic images, image-based, and geometric-based

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Authors: Refilwe Moeletsi

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Dimension stone quarrying around Brits and Belfast areas started in the early 1930s and has been growing rapidly since then. Environmental impacts associated with these quarries have not been documented, and hence this study aims at detecting any change in the environment that might have been caused by these activities. Landsat images that were used to assess land use/land cover changes in Brits quarries from 1998 - 2015. A supervised classification using maximum likelihood classifier was applied to classify each image into different land use/land cover types. Classification accuracy was assessed using Google Earth™ as a source of reference data. Post-classification change detection method was used to determine changes. The results revealed significant increase in granite quarries and corresponding decrease in vegetation cover within the study region.

Keywords: remote sensing, GIS, change detection, granite quarries

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Authors: H. Yousefnia, N. Amraee, M. Hosntalab, S. Zolghadri, A. Bahrami-Samani

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The aim of this study was the preparation of a new agent for bone marrow ablation in patients with multiple myeloma. 166Ho was produced at Tehran research reactor via 165Ho(n,γ)166Ho reaction. Complexion of Ho‐166 with BPAMD was carried out by the addition of about 200µg of BPAMD in absolute water to 1 mci of 166HoCl3 and warming up the mixture 90 0C for 1 h. 166Ho-BPAMD was prepared successfully with radio chemical purity of 95% which was measured by ITLC method. The final solution was injected to wild-type mice and bio distribution was determined up to 48 h. SPECT images were acquired after 2 and 48 h post injection. Both the bio distribution studies and SPECT imaging indicated high bone uptake, while accumulation in other organs was approximately negligible. The results show that 166Ho-BPAMD has suitable characteristics and can be used as a new bone marrow ablative agent.

Keywords: bone marrow ablation, BPAMD, 166Ho, SPECT

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Authors: Ivaylo A. Todorov, Peter S. Boyadzhiev

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A new distinctive species of Stepanovia Kostjukov (Hymenoptera: Eulophidae: Tetrastichinae) was reared in laboratory from mature galls of Diplolepis rosae (Linnaeus) (Cynipidae). The galls were collected from Rosa sp. bushes growing in Osogovo Mt. in Western Bulgaria. The new species is close to Stepanovia rosae Boyadzhiev & Todorov but differs in POL and OOL characteristics, width of antennae, forewings and ovipositor sheaths characteristics, different U-shaped pale stripe above clypeus and the length of the ventral plaque on male antenna. The taxonomically important morphological features are illustrated and compared with the rest species of the genus using Scanning electron microscopy and light reflection by compound microscopy. Images of male genitalia are also prepared.

Keywords: Eulophidae, Diplolepis rosae, galls, Stepanovia osogoviensis, Bulgaria

Procedia PDF Downloads 245

Authors: Deepa, Yashbir Singh, Shi Yi Wu, Michael Friebe, Joao Manuel R. S. Tavares, Hu Wei-Chih

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Cardiovascular disease can be detected by measuring the regional and global wall motion of the left ventricle (LV) of the heart; In this study, we designed a dynamic simulation tool using Computed Tomography (CT) images to assess the difference between actual and simulated left ventricular functions. Thirteen healthy subjects were involved in the study with actual and simulated left ventricular functions. In this research, we found the high correlation between actual left ventricular wall motion and simulated left ventricular wall motion. Our results confirm that our simulation tool is feasible for simulating left ventricular motion.

Keywords: cardiac imaging, left-ventricular remodeling, cardiac wall motion, myocardial functions

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Authors: Qunying Yuan, Manjula Bomma, Adrian Rhoden, Zhigang Xiao

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Selenium is an essential micronutrient for all mammals and plays an important role in maintaining human physiological functions. The potential applications of selenium as food supplements, cancer-prevention, antimicrobial and anti-inflammatory agents have been investigated in biomedicine and food sciences. Nanoscale of selenium is of particular interest due to its better biocompatibility, higher bioavailability, lower toxicity, more homogeneous distribution, and presumptive controlled release of substances. The objective of this study is to explore whether selenium nanoparticle (SeNP) has the potential to be used as a food preservative to reduce food spoilage. SeNPs were synthesized through ascorbic acid reduction of sodium selenite using the bovine serum albumin (BSA) as capping and stabilizing agent. The chemically synthesized SeNPs had a spherical conformation and a size of 22.8 ± 4.7 nm. FTIR analysis confirmed that the nanoparticles were covered with BSA. We further tested the antimicrobial activity of these SeNPs against common food-borne bacteria. Colony forming unit assay showed that SeNPs exhibited good inhibition on the growth of Listeria Monocytogens (ATCC15313), Staphylococcus epidermidis (ATCC 700583) starting at 0.5µg/mL, but only a moderate inhibitory effect on the growth of Staphylococcus aureus (ATCC12600) and Vibrio alginolyticus (ATCC 33787) at a concentration higher than 10µg/mL and 2.5µg/mL, respectively. There was a mild effect against the growth Salmonella enterica (ATCC19585) when the concentration reached 15µg/mL. No inhibition was observed in the growth of Enterococcus faecalis (ATCC 19433). Surprisingly, SeNPs appeared to promote the growth of Vibrio parahaemolyticus (ATCC43996) and Salmonella enterica (ATCC49284) at 30 µg/mL and above. Our preliminary data suggested that the chemically synthesized SeNPs may be able to inhibit some food-borne bacteria, and SeNP as a food preservative should be used with caution. We will explore the mechanisms of the inhibitory action of chemically synthesized SeNPs on bacterial growth and whether the SeNPs are able to inhibit the development of biofilm and antibiotic resistance.

Keywords: antimicrobial, food-borne bacteria, nanoparticles, selenium

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Authors: Jaehong Kim, Sunhee Park, HongSeop Shin, Kyongho Lim, Suhyun Kwon, Don-Gyou Lee, Pureum Kim, Moojong Lim, JongSang Baek

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Transparent displays with OLEDs are the most commonly produced forms of see-through displays on the market or in development. In order to block the visual interruption caused by the light coming from the background, the special panel is combined with transparent displays with OLEDs. There is, however, few studies optical performance of operational shutter panel for transparent displays until now. This paper, therefore, describes the optical performance of operational shutter panels. The novel evaluation method was developed by measuring the amount of light which can form a transmitted background image. The new proposed method could tell how recognize transmitted background images cannot be seen, and is consistent with viewer’s perception.

Keywords: transparent display, operational shutter panel, optical performance, OLEDs

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Authors: Li Zhou, Yanmei Fang

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With current technology, images and videos can be obtained more easily than ever. It is so easy to manipulate these digital multimedia information when obtained, and that the content or source of the image and video could be easily tampered. In this paper, we propose to identify the image and video frame by the texture-based approach, e.g. Markov Transition Probability (MTP), which is in space domain, DCT domain and DWT domain, respectively. In the experiment, image and video frame database is constructed, and is used to train and test the classifier Support Vector Machine (SVM). Experiment results show that the texture-based approach has good performance. In order to verify the experiment result, and testify the universality and robustness of algorithm, we build a random testing dataset, the random testing result is in keeping with above experiment.

Keywords: multimedia forensics, video frame, LBP, MTP, SVM

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Authors: Smita Pallavi, Raj Ratn Pranesh, Sumit Kumar

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Information representation as tables is compact and concise method that eases searching, indexing, and storage requirements. Extracting and cloning tables from parsable documents is easier and widely used; however, industry still faces challenges in detecting and extracting tables from OCR (Optical Character Recognition) documents or images. This paper proposes an algorithm that detects and extracts multiple tables from OCR document. The algorithm uses a combination of image processing techniques, text recognition, and procedural coding to identify distinct tables in the same image and map the text to appropriate the corresponding cell in dataframe, which can be stored as comma-separated values, database, excel, and multiple other usable formats.

Keywords: table extraction, optical character recognition, image processing, text extraction, morphological transformation

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Authors: Shahab Zomorodbakhsh, Hayron Nesa Motevasel

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Water soluble compoundes were attached to single-walled carbon nanotubes (SWNTs) to form water-soluble nano pigments. functionalized SWNTs were then characterized by Fourier Transform Infrared spectroscopy (FT-IR), Raman spectroscopy, UV analysis, Transmission electron microscopy (TEM)and defunctionalization test and Representative results concerning the solubility. The product can be dissolved in water and High-resolution transmission electron microscope images showed that the SWNTs were efficiently functionalized, thus the p-stacking interaction between aromatic rings and COOH of SWNTs was considered responsible for the high solubility and High transmission electron in singlewall nanotubes.

Keywords: functionalized CNTs, singlewalled carbon nanotubes, water soluble compoundes, nano pigments

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Authors: Yi-Chiang Huang, Hsu-Feng Lee, Yu-Chao Tseng, Wen-Yao Huang

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Proton exchange membranes as a key component in fuel cells have been widely studying over the past few decades. As proton exchange, membranes should have some main characteristics, such as good mechanical properties, low oxidative stability and high proton conductivity. In this work, trifluoromethyl groups had been introduced on polymer backbone and phenyl side chain which can provide densely located sulfonic acid group substitution and also promotes solubility, thermal and oxidative stability. Herein, a series of novel sulfonated aromatic hydrocarbon polyelectrolytes was synthesized by polycondensation of 4,4''''-difluoro-3,3''''- bis(trifluoromethyl)-2'',3''-bis(3-(trifluoromethyl)phenyl)-1,1':4',1'':4'',1''':4''',1''''-quinquephenyl with 2'',3''',5'',6''-tetraphenyl-[1,1':4',1'': 4'',1''':4''',1''''-quinquephenyl]-4,4''''-diol and post-sulfonated was through chlorosulfonic acid to given sulfonated polymers (SFC3-X) possessing ion exchange capacities ranging from 1.93, 1.91 and 2.53 mmol/g. ¹H NMR and FT-IR spectroscopy were applied to confirm the structure and composition of sulfonated polymers. The membranes exhibited considerably dimension stability (10-27.8% in length change; 24-56.5% in thickness change) and excellent oxidative stability (weight remain higher than 97%). The mechanical properties of membranes demonstrated good tensile strength on account of the high rigidity multi-phenylated backbone. Young's modulus were ranged 0.65-0.77GPa which is much larger than that of Nafion 211 (0.10GPa). Proton conductivities of membranes ranged from 130 to 240 mS/cm at 80 °C under fully humidified which were comparable or higher than that of Nafion 211 (150 mS/cm). The morphology of membranes was investigated by transmission electron microscopy which demonstrated a clear hydrophilic/hydrophobic phase separation with spherical ionic clusters in the size range of 5-20 nm. The SFC3-1.97 single fuel cell performance demonstrates the maximum power density at 1.08W/cm², and Nafion 211 was 1.24W/cm² as a reference in this work. The result indicated that SFC3-X are good candidates for proton exchange membranes in fuel cell applications. Fuel cell of other membranes is under testing.

Keywords: fuel cells, polyelectrolyte, proton exchange membrane, sulfonated polymers

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Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss

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In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.

Keywords: recognition, handwriting, Arabic text, HMMs, embedded training

Procedia PDF Downloads 354

Authors: Hee-Choul Kwon, Heeyong Kwon

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Image rotation is one of main pre-processing steps for image processing or image pattern recognition. It is implemented with a rotation matrix multiplication. It requires a lot of floating point arithmetic operations and trigonometric calculations, so it takes a long time to execute. Therefore, there has been a need for a high speed image rotation algorithm without two major time-consuming operations. However, the rotated image has a drawback, i.e. distortions. We solved the problem using an augmented two-step shear transform. We compare the presented algorithm with the conventional rotation with images of various sizes. Experimental results show that the presented algorithm is superior to the conventional rotation one.

Keywords: high-speed rotation operation, image rotation, transform matrix, image processing, pattern recognition

Procedia PDF Downloads 277

Authors: Ibrahim Rassoul, A. Serir, E-K. Si Ahmed, J. Legrand

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The acronym PEM refers to Proton Exchange Membrane or alternatively Polymer Electrolyte Membrane. Due to its high efficiency, low operating temperature (30–80 °C), and rapid evolution over the past decade, PEMFCs are increasingly emerging as a viable alternative clean power source for automobile and stationary applications. Before PEMFCs can be employed to power automobiles and homes, several key technical challenges must be properly addressed. One technical challenge is elucidating the mechanisms underlying water transport in and removal from PEMFCs. On one hand, sufficient water is needed in the polymer electrolyte membrane or PEM to maintain sufficiently high proton conductivity. On the other hand, too much liquid water present in the cathode can cause “flooding” (that is, pore space is filled with excessive liquid water) and hinder the transport of the oxygen reactant from the gas flow channel (GFC) to the three-phase reaction sites. The experimental transparent fuel cell used in this work was designed to represent actual full scale of fuel cell geometry. According to the operating conditions, a number of flow regimes may appear in the microchannel: droplet flow, blockage water liquid bridge /plug (concave and convex forms), slug/plug flow and film flow. Some of flow patterns are new, while others have been already observed in PEMFC microchannels. An algorithm in MATLAB was developed to automatically determine the flow structure (e.g. slug, droplet, plug, and film) of detected liquid water in the test microchannels and yield information pertaining to the distribution of water among the different flow structures. A video processing algorithm was developed to automatically detect dynamic and static liquid water present in the gas channels and generate relevant quantitative information. The potential benefit of this software allows the user to obtain a more precise and systematic way to obtain measurements from images of small objects. The void fractions are also determined based on images analysis. The aim of this work is to provide a comprehensive characterization of two-phase flow in an operating fuel cell which can be used towards the optimization of water management and informs design guidelines for gas delivery microchannels for fuel cells and its essential in the design and control of diverse applications. The approach will combine numerical modeling with experimental visualization and measurements.

Keywords: polymer electrolyte fuel cell, air-water two phase flow, gas diffusion layer, microchannels, advancing contact angle, receding contact angle, void fraction, surface tension, image processing

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Authors: Mohsen Maraoui

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In the face of the growth in the quantity of data produced, several methods and techniques appear to remedy the problems of processing and analyzing large amounts of information mainly in the field of teaching. In this paper, we propose an intelligent cloud-based teaching system for E-learning content services. This system makes easy the manipulation of various educational content forms, including text, images, videos, 3 dimensions objects and scenes of virtual reality and augmented reality. We discuss the integration of institutional and external services to provide personalized assistance to university members in their daily activities. The proposed system provides an intelligent solution for media services that can be accessed from smart devices cloud-based intelligent service environment with a fully integrated system.

Keywords: cloud computing, e-learning, indexation, IoT, learning in Arabic language, smart tools

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Authors: Grishma D. Solanki, Karshan Kandoriya

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In modern era of information age, digitalization has revolutionized like never before. Powerful computers, advanced photo editing software packages and high resolution capturing devices have made manipulation of digital images incredibly easy. As per as image forensics concerns, one of the most actively researched area are detection of copy move forgeries. Higher computational complexity is one of the major component of existing techniques to detect such tampering. Moreover, copy move forgery is usually performed in three steps. First, copying of a region in an image then pasting the same one in the same respective image and finally doing some post-processing like rotation, scaling, shift, noise, etc. Consequently, pseudo Zernike moment is used as a features extraction method for matching image blocks and as a primary factor on which performance of detection algorithms depends.

Keywords: copy-move image forgery, digital forensics, image forensics, image forgery

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Authors: Qiaosi Li, Frankie Kwan Kit Wong, Tung Fung

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Lightweight unmanned aerial vehicle (UAV) loading with novel sensors offers a low cost approach for data acquisition in complex environment. This study established a framework for applying UAV system in complex environment quick mapping and assessed the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area Mai Po Inner Deep Bay Ramsar Site, Hong Kong. The study area was part of shallow bay with flat terrain and the major species including reedbed and four mangroves: Kandelia obovata, Aegiceras corniculatum, Acrostichum auerum and Acanthus ilicifolius. Other species involved in various graminaceous plants, tarbor, shrub and invasive species Mikania micrantha. In particular, invasive species climbed up to the mangrove canopy caused damage and morphology change which might increase species distinguishing difficulty. Hyperspectral images were acquired by Headwall Nano sensor with spectral range from 400nm to 1000nm and 0.06m spatial resolution image. A sequence of multi-view RGB images was captured with 0.02m spatial resolution and 75% overlap. Hyperspectral image was corrected for radiative and geometric distortion while high resolution RGB images were matched to generate maximum dense point clouds. Furtherly, a 5 cm grid digital surface model (DSM) was derived from dense point clouds. Multiple feature reduction methods were compared to identify the efficient method and to explore the significant spectral bands in distinguishing different species. Examined methods including stepwise discriminant analysis (DA), support vector machine (SVM) and minimum noise fraction (MNF) transformation. Subsequently, spectral subsets composed of the first 20 most importance bands extracted by SVM, DA and MNF, and multi-source subsets adding extra DSM to 20 spectrum bands were served as input in maximum likelihood classifier (MLC) and SVM classifier to compare the classification result. Classification results showed that feature reduction methods from best to worst are MNF transformation, DA and SVM. MNF transformation accuracy was even higher than all bands input result. Selected bands frequently laid along the green peak, red edge and near infrared. Additionally, DA found that chlorophyll absorption red band and yellow band were also important for species classification. In terms of 3D data, DSM enhanced the discriminant capacity among low plants, arbor and mangrove. Meanwhile, DSM largely reduced misclassification due to the shadow effect and morphological variation of inter-species. In respect to classifier, nonparametric SVM outperformed than MLC for high dimension and multi-source data in this study. SVM classifier tended to produce higher overall accuracy and reduce scattered patches although it costs more time than MLC. The best result was obtained by combining MNF components and DSM in SVM classifier. This study offered a precision species distribution survey solution for inaccessible wetland area with low cost of time and labour. In addition, findings relevant to the positive effect of DSM as well as spectral feature identification indicated that the utility of UAV-borne hyperspectral and photogrammetry deriving 3D data is promising in further research on wetland species such as bio-parameters modelling and biological invasion monitoring.

Keywords: digital surface model (DSM), feature reduction, hyperspectral, photogrammetric point cloud, species mapping, unmanned aerial vehicle (UAV)

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Authors: Akash Amalan, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang

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Federated learning is an emerging concept in the domain of distributed machine learning. This concept has enabled General Adversarial Networks (GANs) to benefit from the rich distributed training data while preserving privacy. However, in a non-IID setting, current federated GAN architectures are unstable, struggling to learn the distinct features, and vulnerable to mode collapse. In this paper, we propose an architecture MULTI-FLGAN to solve the problem of low-quality images, mode collapse, and instability for non-IID datasets. Our results show that MULTI-FLGAN is four times as stable and performant (i.e., high inception score) on average over 20 clients compared to baseline FLGAN.

Keywords: federated learning, generative adversarial network, inference attack, non-IID data distribution

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Authors: Carolina Brandão Piva

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In our visual culture, images play a newly significant role in the basis of a complex dialogue between imagination, creativity, and social practice. Insofar as imagination has broken out of the 'special expressive space of art' to become a part of the quotidian mental work of ordinary people, it is pertinent to recognize that visual representation can no longer be assumed as if in a domain detached from everyday life or exclusively 'centered' within the limited frame of 'art history.' The approach of Visual Culture as a field of study is, in this sense, indispensable to comprehend that not only 'the image,' but also 'the imagined' and 'the imaginary' are produced in the plurality of social interactions; crucial enough, this assertion directs us to something new in contemporary cultural processes, namely both imagination and image production constitute a social practice. This paper starts off with this approach and seeks to examine the artistic practice of two women from the State of Goiás, Brazil, who are ordinary citizens with their daily activities and narratives but also dedicated to visuality production. With no formal training from art schools, branded or otherwise, Maria Aparecida de Souza Pires deploys 'waste disposal' of daily life—from car tires to old work clothes—as a trampoline for art; also adept at sourcing raw materials collected from her surroundings, she manipulates raw hewn wood, tree trunks, plant life, and various other pieces she collects from nature giving them new meaning and possibility. Hilda Freire works with sculptures in clay using different scales and styles; her art focuses on representations of women and pays homage to unprivileged groups such as the practitioners of African-Brazilian religions, blue-collar workers, poor live-in housekeepers, and so forth. Although they have never been acknowledged by any mainstream art institution in Brazil, whose 'criterion of value' still favors formally trained artists, Maria Aparecida de Souza Pires, and Hilda Freire have produced visualities that instigate 'new ways of seeing,' meriting cultural significance in many ways. Their artworks neither descend from a 'traditional' medium nor depend on 'canonical viewing settings' of visual representation; rather, they consist in producing relationships with the world which do not result in 'seeing more,' but 'at least differently.' From this perspective, the paper finally demonstrates that grouping this kind of artistic production under the label of 'mere craft' has much more to do with who is privileged within the fields of power in art system, who we see and who we do not see, and whose imagination of what is fed by which visual images in Brazilian contemporary society.

Keywords: visual culture, artistic practice, women's art in the Brazilian State of Goiás, Maria Aparecida de Souza Pires, Hilda Freire

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Authors: Bing Gu

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Abstract—Most of Conventional facial recognition systems are based on image features, such as LBP, SIFT. Recently some DBN-based 2D facial recognition systems have been proposed. However, we find there are few DBN-based 3D facial recognition system and relative researches. 3D facial images include all the individual biometric information. We can use these information to build more accurate features, So we present our DBN-based face recognition system using Light Field. We can see Light Field as another presentation of 3D image, and Light Field Camera show us a way to receive a Light Field. We use the commercially available Light Field Camera to act as the collector of our face recognition system, and the system receive a state-of-art performance as convenient as conventional 2D face recognition system.

Keywords: DBN, face recognition, light field, Lytro

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Authors: Simone F. Medeiros, Jessica M. Fonseca, Gizelda M. Alves, Danilo M. Santos, Sérgio P. Campana-Filho, Amilton M. Santos

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Stimuli responsive and biocompatible hydrogel nanoparticles have gained special attention as systems for potential applications in controlled release of drugs to improve their therapeutic efficacy while minimizing side effects. In this work, novel solid dispersions based on thermo- and pH-responsive poly(N-vinylcaprolactam-co-itaconic acid-co-ethylene- glycol dimethacrylate) hydrogel nanoparticles embedded in chitosan matrices were prepared via spray drying for controlled release of ketoprofen. Firstly, the hydrogel nanoparticles containing ketoprofen were prepared via precipitation polymerization and their stimuli-responsive behavior, thermal properties, chemical composition, encapsulation efficiency and morphology were characterized. Then, hydrogel nanoparticles with different particles size were embedded into chitosan matrices via spray-drying. Scanning electron microscopy (SEM) analyses were performed to investigate the particles size, dispersity and morphology. Finally, ketoprofen release profiles were studied as a function of pH and temperature. Chitosan/poly(NVCL-co-IA-co-EGDMA)-ketoprofen microparticles presented spherical shape, rough surface and pronounced agglomeration, indicating that hydrogels nanoparticles loaded with ketoprofen modified the surface of chitosan matrix. The maximum encapsulation efficiency of ketoprofen into hydrogel nanoparticles was 57.8% and the electrostatic interactions between amino groups from chitosan and carboxylic groups from hydrogel nanoparticles were able to control ketoprofen release. The hydrogel nanoparticles themselves were capable to retard the release of ketoprofen-loaded until 48h of in vitro release tests, while their incorporation into chitosan matrix achieved a maximum percentage of drug release of 45%, using a mass ratio of chitosan: poly(NVCL-co-IA-co-EGDMA equal to 10:7, and 69%, using a mass ratio of chitosan: poly(NVCL-co-IA-co-EGDMA equal to 5:2.

Keywords: hydrogel nanoparticles, poly(N-vinylcaprolactam-co-itaconic acid-co-ethylene- glycol dimethacrylate), chitosan, ketoprofen, spray-drying

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Authors: Nilüfer Yıldız Varan

Abstract:

The antimicrobial activities of chitosan against various bacteria and fungi are well known, and the antimicrobial activity of chitosan depends on pH. This study investigates the antimicrobial activity at different pH levels. Nylon 6,6 fabrics were treated with different chitosan solutions. Additionally, samples were treated also in basic conditions to see the antimicrobial activities. AATCC Test Method 100 was followed to evaluate the antimicrobial activity using Staphylococcus aureus ATCC 6538 test inoculum. The pH of the chitosan solutions was controlled below 6.5 since chitosan shows its antimicrobial activity only in acidic conditions because of its poor solubility above 6.5. In basic conditions, the samples did not show any antimicrobial activity. It appears from SEM images that the bonded chitosan in the structures exists. In acidic media (ph < 6.5), all samples showed antimicrobial activity. No correlation was found between pH levels and antimicrobial activity in acidic media.

Keywords: chitosan, nylon 6, 6, crosslinking, pH stability, antimicrobial

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Authors: Khalid Omari, Rene Chenier, Enrique Blondel, Ryan Ahola

Abstract:

Northern Canadian coasts have vulnerable and very dynamic intertidal zones with very high tides occurring in several areas. The impact of climate change presents challenges not only for maintaining this biodiversity but also for navigation safety adaptation due to the high sediment mobility in these coastal areas. Thus, frequent mapping of shorelines and intertidal changes is of high importance. To help in quantifying the changes in these fragile ecosystems, remote sensing provides practical monitoring tools at local and regional scales. Traditional methods based on high-resolution optical sensors are often used to map intertidal areas by benefiting of the spectral response contrast of intertidal classes in visible, near and mid-infrared bands. Tidal areas are highly reflective in visible bands mainly because of the presence of fine sand deposits. However, getting a cloud-free optical data that coincide with low tides in intertidal zones in northern regions is very difficult. Alternatively, the all-weather capability and daylight-independence of the microwave remote sensing using synthetic aperture radar (SAR) can offer valuable geophysical parameters with a high frequency revisit over intertidal zones. Multi-polarization SAR parameters have been used successfully in mapping intertidal zones using incoherence target decomposition. Moreover, the crustal displacements caused by ocean tide loading may reach several centimeters that can be detected and quantified across differential interferometric synthetic aperture radar (DInSAR). Soil moisture change has a significant impact on both the coherence and the backscatter. For instance, increases in the backscatter intensity associated with low coherence is an indicator for abrupt surface changes. In this research, we present primary results obtained following our investigation of the potential of the fully polarimetric Radarsat-2 data for mapping an inter-tidal zone located on Tasiujaq on the south-west shore of Ungava Bay, Quebec. Using the repeat pass cycle of Radarsat-2, multiple seasonal fine quad (FQ14W) images are acquired over the site between 2016 and 2018. Only 8 images corresponding to low tide conditions are selected and used to build an interferometric stack of data. The observed displacements along the line of sight generated using HH and VV polarization are compared with the changes noticed using the Freeman Durden polarimetric decomposition and Touzi degree of polarization extrema. Results show the consistency of both approaches in their ability to monitor the changes in intertidal zones.

Keywords: SAR, degree of polarization, DInSAR, Freeman-Durden, polarimetry, Radarsat-2

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Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda

Abstract:

In this work we present an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods: the parameters of distribution, the moments centered of the different projections and the Barr features. It should be noted that these methods are applied on segments gotten after the division of the binary image of the word in six segments. The classification is achieved by a multi layers perceptron. Detailed experiments are carried and satisfactory recognition results are reported.

Keywords: handwritten word recognition, neural networks, image processing, pattern recognition, features extraction

Procedia PDF Downloads 513

Authors: Srikanta Tagore Sarkar, Prasanta Kumar Mandal, Dibakar Roy

Abstract:

The association of a capitate fracture with a scaphoid fracture has been termed as the naviculocapitate syndrome. The existence of some nondisplaced fractures of scaphoid and capitate with or without the fracture of lunate or radius suggests that there is a spectrum of these injuries, and this confuses the terminology. With our case; we report an unusual variety of this naviculocapitate syndrome with distal radial Colles fracture in addition to the nondisplaced fractures of the scaphoid, capitate and the dorsal lip of radial fracture. When we looked at the literature there is no another Colles fracture reported together with undisplaced scapho-capitate syndrome. The coronal and sagittal images that obtained from the MDCT (Multidetector computed tomography) is useful and effective imaging modality to diagnose complex wrist fractures with more details that are not detected in X-rays.

Keywords: scaphoid, capitate, Colles’ fracture, syndrome, MDCT, unusual

Procedia PDF Downloads 393

Authors: Mohammadhosein Rahimi, Mohammad Raouf Hosseini, Mehran Bakhshi, Alireza Baghbanan

Abstract:

Silver ions (Ag⁺) and their compounds are consequentially toxic to microorganisms, showing biocidal effects on many species of bacteria. Silver-phosphate (or silver orthophosphate) is one of these compounds, which is famous for its antimicrobial effect and catalysis application. In the present study, a green method was presented to synthesis silver-phosphate nanoparticles using Sporosarcina pasteurii. The composition of the biosynthesized nanoparticles was identified as Ag₃PO₄ using X-ray Diffraction (XRD) and Energy Dispersive Spectroscopy (EDS). Also, Fourier Transform Infrared (FTIR) spectroscopy showed that Ag₃PO₄ nanoparticles was synthesized in the presence of biosurfactants, enzymes, and proteins. In addition, UV-Vis adsorption of the produced colloidal suspension approved the results of XRD and FTIR analyses. Finally, Transmission Electron Microscope (TEM) images indicated that the size of the nanoparticles was about 20 nm.

Keywords: bacteria, biosynthesis, silver-phosphate, Sporosarcina pasteurii, nanoparticle

Procedia PDF Downloads 449