Publicado en: Sensors
Structure-From-Motion Approach for Characterization of Bioerosion Patterns Using UAV Imagery
Genchi, S. A., Vitale, A. J., Perillo, G. M., & Delrieux, C. A. (2015)
The aim of this work is to evaluate the applicability of the 3D model obtained through Structure-from-Motion (SFM) from unmanned aerial vehicle (UAV) imagery, in order to characterize bioerosion patterns (i.e., cavities for roosting and nesting) caused by burrowing parrots on a cliff in Bahía Blanca, Argentina. The combined use of SFM-UAV technology was successfully applied for the 3D point cloud model reconstruction. The local point density, obtained by means of a sphere of radius equal to 0.5 m, reached a mean value of 9749, allowing to build a high-resolution model (0.013 m) for resolving fine spatial details in topography. To test the model, we compared it with another point cloud dataset which was created using a low cost do-it-yourself terrestrial laser scanner; the results showed that our georeferenced model had a good accuracy. In addition, an innovative method for the detection of the bioerosion features was implemented, through the processing of data provided by SFM like color and spatial coordinates (particularly the y coordinate). From the 3D model, we also derived topographic calculations such as slope angle and surface roughness, to get associations between the surface topography and bioerosion features.
Structure-from-Motion Approach, unmanned aerial vehicle, 3D point cloud, topography, bioerosion, burrowing parrot
Publicado en: EURASIP Journal on Image and Video Processing
Multifractal characterisation and classification of bread crumb digital images
Baravalle, R. G., Delrieux, C. A., & Gómez, J. C. (2015)
Adequate models of the bread crumb structure can be critical for understanding flow and transport processes in bread manufacturing, creating synthetic bread crumb images for photo-realistic rendering, evaluating similarities, and establishing quality features of different bread crumb types. In this article, multifractal analysis, employing the multifractal spectrum (MFS), has been applied to study the structure of the bread crumb in four varieties of bread (baguette, sliced, bran, and sandwich). The computed spectrum can be used to discriminate among bread crumbs from different types. Also, high correlations were found between some of these parameters and the porosity, coarseness, and heterogeneity of the samples. These results demonstrate that the MFS is an appropriate tool for characterising the internal structure of the bread crumb, and thus, it may be used to establish important quality properties it should have. The MFS has shown to provide local and global image features that are both robust and low-dimensional, leading to feature vectors that capture essential information for classification tasks. Results show that the MFS-based classification is able to distinguish different bread crumbs with very high accuracy. Multifractal modelling of the underlying structure can be an appropriate method for parameterising and simulating the appearance of different bread crumbs.
Fractal Multifractal Image analysis Image classification Feature extraction
Publicado en: Phyton, International Journal of Experimental Botany
Analyzing digital color descriptors in wheat
Salomón, N., Misller, V., Delrieux, C., & Miranda, R. (2016)
Color is one of the factors used in quality estimation in many agricultural and food products. Currently, the evaluation of color depends on judgments made by human experts. These are subjective and inevitably affected by physical, physiological and environmental conditions. Suitable instrumental is required to provide objectivity and coherence to color measurements and quantitative expressions. It would be very useful to have tools that allow both practical and precise approaches to chromatic evaluation of products for human consumption. This work suggests a methodology which might contribute to solve that constraint and the analysis of environmental influences on this character in two consecutive wheat growing seasons. This research used 18 cultivars, which were sampled in two crop growth stages. On the first part of this study, a spectrophotometer and a digital camera were used for the analysis of color at the phenological state of tillering. Data analysis showed a correlation between both study methodologies, which would make more practical the work of breeders during data collection. The second part of the study of the genotype-environment interaction (GEI) continued using only a digital camera. The phenological state of tillering did not evidence amarked GEI. On the other hand, an appreciable GEI was found at physiological ripeness.
Wheat; Color; Digital image; Spectrophotometer; Genotype-environment interaction;
Publicado en: Computers & Graphics
Procedural Bread Making
Baravalle, R., Patow, G. A., & Delrieux, C. (2015)
Accurate modeling and rendering of food, and in particular of bread and other baked edible stuff, have not received as much attention as other materials in the photorealistic rendering literature. In particular, bread turns out to be a structurally complex material, and the eye is very precise in spotting improper models, making adequate bread modeling a difficult task. In this paper we present an accurate computational bread making model that allows us to faithfully represent the geometrical structure and the appearance of bread through its making process. This is achieved by a careful simulation of the conditions during proving and baking to get realistically looking bread. Our results are successfully compared to real bread by both visual inspection and by a multifractal-based error metric.
Bread ,Photorealism, Fractal, Procedural models
Publicado en: Computer Graphics Forum
Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting
Diehl, A., Pelorosso, L., Delrieux, C., Saulo, C., Ruiz, J., Gröller, M. E., & Bruckner, S. (2015, June)
Weather conditions affect multiple aspects of human life such as economy, safety, security, and social activities. For this reason, weather forecast plays a major role in society. Currently weather forecasts are based on Numerical Weather Prediction (NWP) models that generate a representation of the atmospheric flow. Interactive visualization of geo-spatial data has been widely used in order to facilitate the analysis of NWP models. This paper presents a visualization system for the analysis of spatio-temporal patterns in short-term weather forecasts. For this purpose, we provide an interactive visualization interface that guides users from simple visual overviews to more advanced visualization techniques. Our solution presents multiple views that include a timeline with geo-referenced maps, an integrated webmap view, a forecast operation tool, a curve-pattern selector, spatial filters, and a linked meteogram. Two key contributions of this work are the timeline with geo-referenced maps and the curve-pattern selector. The latter provides novel functionality that allows users to specify and search for meaningful patterns in the data. The visual interface of our solution allows users to detect both possible weather trends and errors in the weather forecast model. We illustrate the usage of our solution with a series of case studies that were designed and validated in collaboration with domain experts.
Structure-from-Motion Approach, unmanned aerial vehicle, 3D point cloud, topography, bioerosion, burrowing parrot
Publicado en: Geomorphology
Methodology for classification of geographical features with remote sensing images: Application to tidal flats
Sarmiento, G. R., Cipolletti, M. P., Perillo, M. M., Delrieux, C. A., & Perillo, G. M. (2016)
Tidal flats generally exhibit ponds of diverse size, shape, orientation and origin. Studying the genesis, evolution, stability and erosive mechanisms of these geographic features is critical to understand the dynamics of coastal wetlands. However, monitoring these locations through direct access is hard and expensive, not always feasible, and environmentally damaging. Processing remote sensing images is a natural alternative for the extraction of qualitative and quantitative data due to their non-invasive nature. In this work, a robust methodology for automatic classification of ponds and tidal creeks in tidal flats using Google Earth images is proposed. The applicability of our method is tested in nine zones with different morphological settings. Each zone is processed by a segmentation stage, where ponds and tidal creeks are identified. Next, each geographical feature is measured and a set of shape descriptors is calculated. This dataset, together with a-priori classification of each geographical feature, is used to define a regression model, which allows an extensive automatic classification of large volumes of data discriminating ponds and tidal creeks against other various geographical features. In all cases, we identified and automatically classified different geographic features with an average accuracy over 90% (89.7% in the worst case, and 99.4% in the best case). These results show the feasibility of using freely available Google Earth imagery for the automatic identification and classification of complex geographical features. Also, the presented methodology may be easily applied in other wetlands of the world and perhaps employing other remote sensing imagery.
Ponds; Tidal courses; Object detection; Classification; Shape descriptors
Publicado en: Ecotoxicology and environmental safety
Evaluation of sublethal effects of polymer-based essential oils nanoformulation on the german cockroach
González, J. W., Yeguerman, C., Marcovecchio, D., Delrieux, C., Ferrero, A., & Band, B. F. (2016)
The German cockroach, Blattella germanica (L.), is a serious household and public health pest worldwide. The aim of the present study was to evaluate the sublethal activity of polymer-based essential oils (EOs) nanoparticles (NPs) on adults of B. germanica. The LC50 and LC25 for contact toxicity were determined. To evaluate the repellency of EOs and NPs at LC25, a software was specially created in order to track multiple insects on just-recorded videos, and generate statistics using the obtained information. The effects of EOs and NPs at LC25 and LC50 on the nutritional physiology were also evaluated. The results showed that NPs exerted sublethal effects on the German cockroach, since these products enhance the repellent effects of the EOs and negatively affected the nutritional indices and the feeding deterrence index.
Blatella germanica; Polymer-based nanoparticles; Geranium and bergamot essential oils; Repellency; Nutritional physiology
Publicado en: Computer Animation and Virtual Worlds
Realistic modeling of porous materials.
Baravalle, R., Scandolo, L., Delrieux, C., García Bauza, C., & Eisemann, E. (2016)
Photorealistic modeling and rendering of materials with complex internal mesostructure is a hard challenge in Computer Graphics. In particular, macroscopic porous materials consist of complex translucent substances that exhibit different details and light interaction at several different scales. State-of-the-art techniques for modeling porous materials manage the material either as a surface and set up complex capture procedures or as a volume by employing different instances of procedural noise models for its representation. While the surface solution achieves several desired material properties, it still presents drawbacks in practical applications—high computational costs, complex capture procedures, and poor image variability, among others. Volumetric solutions are more flexible, but the final structure and appearance are difficult to control. To overcome these drawbacks, we propose an algorithm for the procedural generation of porous materials. The method is based on an artistic and physically inspired simulation of the growth of self-avoiding bubbles inside a volume, by means of dynamical systems. The patterns induced by the bubbles can be easily and intuitively controlled. The bubbles adapt to any given shape and have convincing global and local fluid-like patterns as seen in bread and sponges. Our method generates 3D textures that adequately represent porous materials, which can be used as input for creating realistic renderings of different porous objects. As a case study, we present the results of using these 3D textures as input to a direct volume renderer and show that they compare favorably with standard 3D texture synthesis methods.
porous materials; dynamical systems; photorealism
Publicado en: The Visual Computer
ITEA—interactive trajectories and events analysis: exploring sequences of spatio-temporal events in movement data
Cibulski, L., Gračanin, D., Diehl, A., Splechtna, R., Elshehaly, M., Delrieux, C., & Matković, K. (2016)
Widespread use of GPS and similar technologies makes it possible to collect extensive amounts of trajectory data. These data sets are essential for reasonable decision making in various application domains. Additional information, such as events taking place along a trajectory, makes data analysis challenging, due to data size and complexity. We present an integrated solution for interactive visual analysis and exploration of events along trajectories data. Our approach supports analysis of event sequences at three different levels of abstraction, namely spatial, temporal, and events themselves. Customized views as well as standard views are combined to form a coordinated multiple views system. In addition to trajectories and events, we include on-the-fly derived data in the analysis. We evaluate our integrated solution using the IEEE VAST 2015 Challenge data set. A successful detection and characterization of malicious activity indicate the usefulness and efficiency of the presented approach.
Interactive visual analysis, Movement data, Spatio-temporal data, Coordinated multiple views
Publicado en: Marine Geology
Automatic methodology for mapping of coastal zones in video sequences.
Revollo, N. V., Delrieux, C. A., & Perillo, G. M. (2016)
Gathering precise and detailed geomorphological and dynamic information of coastal processes is increasingly required for environmental studies and coastal management policies as well. Traditional methods for in situ measurements, or remote sensing monitoring by satellites or airbone imagery, impose limitations and tradeoffs between image quality, operational costs, availability, and negative environmental effects. These limitations and tradeoffs restrict the kind of environmental studies that can be undertaken, specifically when a high spatial and temporal resolution is required over wide geographical areas. In the last decades, video monitoring systems have demonstrated to be a cost-effective alternative for this and other similar purposes. Notwithstanding that, video processing is not fully mature in the context of environmental monitoring in general, and, thus, most of the past and current efforts have been developed in an ad hoc basis. This has the drawback that most available solutions are hardly useful in contexts different from their original setup. In this work we develop an autonomous application for geographic feature extraction and recognition in coastal videos. Specifically, we address the classification and feature measurement of multiple beach zones, a topic addressed to a lesser extent by other projects. The system is designed to be deployed in inexpensive, off-the-shelf hardware, and open source software development frameworks, in a way such that the results can be easily replicated by other research groups. The initial setup and calibration requires very simple supervision, thus allowing the system to be used in a variety of coastal environments.v
Coastal analysis software; Environmental monitoring; Beach management; Image processing; Feature extraction
Publicado en: Ocean & Coastal Management
Beach carrying capacity assessment through image processing tools for coastal management
Cisneros, M. A. H., Sarmiento, N. V. R., Delrieux, C. A., Piccolo, M. C., & Perillo, G. M. (2016)
Coastal environments are spaces where people may develop varied economic and recreational activities, such as tourism, which usually damage beaches and other natural resources commonly placed in these settings. The aim of this paper is to present a methodology to estimate and evaluate the Beach Carrying Capacity (BCC) and the actual beach usage level in coastal cities, using on-site information and video processing to provide significant real-time data. To test our methodology, we chose the coastal city of Monte Hermoso, Argentina, as a pilot site because it is by far the prime choice for a large population during summer vacation in this country. Initially, to estimate BCC, cartographic information about facilities and beach zones was collected and combined with surveys requested to tourists, to better understand their habits and preferences. This allowed an accurate estimation of other beach capacities related to BCC. Secondly, beach video sequences were processed with an algorithm that identified, located and counted people on the beach with an adequate accuracy. The actual occupancy factor was computed and used to asses whether the BCC had been exceeded. Also, people were tracked and their preferred relaxing areas were registered (e.g, closer to seaside during the morning). Finally, all the information was stored and visualized using a Geographic Information System (GIS) which allows both to analyze the different information layers and to produce interactive thematic maps. In this way, the resulting methodology may help to identify zones under risk of deterioration and to define suitable places for the development of varied activities (specially those related to tourism). It may also serve as a dashboard for decision and policy making and contribute to coastal management planning as well.
Image processing; Coastal software; Coastal management; Feature extraction; Beach Carrying Capacity; Geographic Information Systems
Publicado en: Clinical oral investigations
Multifractal spectrum and lacunarity as measures of complexity of osseointegration
De Souza Santos, D., dos Santos, L. C. B., Carvalho, A. D. A. T., Leão, J. C., Delrieux, C., Stosic, T., & Stosic, B. (2016)
Fractal, multifractal, and lacunarity analysis are performed on scanning electron microscopy (SEM) images of titanium implants that were first subjected to different treatment combinations of i) sand blasting, ii) acid etching, and iii) exposition to calcium phosphate, and were then submersed in a simulated body fluid (SBF) for 30 days. All the three numerical techniques are applied to the implant SEM images before and after SBF immersion, in order to provide a comprehensive set of common quantitative descriptors. It is found that implants subjected to different physicochemical treatments before submersion in SBF exhibit a rather similar level of complexity, while the great variety of crystal forms after SBF submersion reveals rather different quantitative measures (reflecting complexity), for different treatments. In particular, it is found that acid treatment, in most combinations with the other considered treatments, leads to a higher fractal dimension (more uniform distribution of crystals), lower lacunarity (lesser variation in gap sizes), and narrowing of the multifractal spectrum (smaller fluctuations on different scales). The current quantitative description has shown the capacity to capture the main features of complex images of implant surfaces, for several different treatments. Such quantitative description should provide a fundamental tool for future large scale systematic studies, considering the large variety of possible implant treatments and their combinations. Quantitative description of early stages of osseointegration on titanium implants with different treatments should help develop a better understanding of this phenomenon, in general, and provide basis for further systematic experimental studies. Clinical practice should benefit from such studies in the long term, by more ready access to implants of higher quality.
Dental implants,Osseointegration,Fractal dimension,Multifractal spectrum,Lacunarity
Publicado en: Medical Physics
A new algorithm for estimating the rod volume fraction and the trabecular thickness from in vivo computed tomography
Thomsen, F. S. L., Peña, J. A., Lu, Y., Huber, G., Morlock, M., Glüer, C. C., & Delrieux, C. A. (2016)
Existing microstructure parameters are able to predict vertebral in vitro failure load, but for noisy in vivo data more complex algorithms are needed for a robust assessment. A new algorithm is proposed for the microstructural analysis of trabecular bone under in vivoquantitative computed tomography (QCT). Five fractal parameters are computed: (1) the average local fractal dimension FD, (2) its standard deviation FD.SD, (3) the fractal rod volume ratio fRV/BV, (4) the average fractal trabecular thickness fTb.Th, and (5) its coefficient of variation fTb.Th.CV. The algorithm requires neither an explicit skeletonization of the trabecular bone, nor a well-defined transition between bone and marrow phases. Two experiments were conducted to compare the fractal with established microstructural parameters. In the first, 20 volumes-of-interest of embedded vertebrae phantoms were scanned five times under QCT and high-resolution (HR-)QCT and once under peripheral HRQCT (HRpQCT), to derive accuracy and precision. In the second experiment, correlations between in vitro HRQCT structural parameters were obtained from 76 human T11, T12, or L1 vertebrae. In vitro fracture data were available for a subset of 17 human T12 vertebrae so that linear regression models between failure load and microstructural HRQCT parameters could be analyzed. The results showed correlations of fTb.Th and fRV/BV with their nonfractal pendants trabecular thickness (Tb.Th) and respective structure model index (SMI) while higher precision and accuracy was observed on the fractal measures. Linear models of bone mineral density with two and three fractal microstructural HRQCT parameters explained 86% and 90% (adjusted R2) of the failure load and significantly improved the linear models based only on BMD and established standard microstructural parameters (68%–77% adjusted R2). The application of fractal methods may grant further insight into the study of bone quality in vivowhen image resolution and quality are less than optimal for current standard methods.
bone; computerised tomography; fractals; image resolution; image thinning; medical image processing; phantoms; regression analysis
Publicado en: International Journal of Computer Assisted Radiology and Surgery, 1-10.
Local texture descriptors for the assessment of differences in diffusion magnetic resonance imaging of the brain
Thomsen, F. S. L., Delrieux, C. A., & de Luis-García, R. (2016)
Descriptors extracted from magnetic resonance imaging (MRI) of the brain can be employed to locate and characterize a wide range of pathologies. Scalar measures are typically derived within a single-voxel unit, but neighborhood-based texture measures can also be applied. In this work, we propose a new set of descriptors to compute local texture characteristics from scalar measures of diffusion tensor imaging (DTI), such as mean and radial diffusivity, and fractional anisotropy. We employ weighted rotational invariant local operators, namely standard deviation, inter-quartile range, coefficient of variation, quartile coefficient of variation and skewness. Sensitivity and specificity of those texture descriptors were analyzed with tract-based spatial statistics of the white matter on a diffusion MRI group study of elderly healthy controls, patients with mild cognitive impairment (MCI), and mild or moderate Alzheimer’s disease (AD). In addition, robustness against noise has been assessed with a realistic diffusion-weighted imaging phantom and the contamination of the local neighborhood with gray matter has been measured. The new texture operators showed an increased ability for finding formerly undetected differences between groups compared to conventional DTI methods. In particular, the coefficient of variation, quartile coefficient of variation, standard deviation and inter-quartile range of the mean and radial diffusivity detected significant differences even between previously not significantly discernible groups, such as MCI versus moderate AD and mild versus moderate AD. The analysis provided evidence of low contamination of the local neighborhood with gray matter and high robustness against noise. The local operators applied here enhance the identification and localization of areas of the brain where cognitive impairment takes place and thus indicate them as promising extensions in diffusion MRI group studies.
Local texture Diffusion tensor imaging Alzheimer’s disease White matter
Publicado en: IET Computer Vision
A novel set of Bilateral and Radial Symmetry Shape Descriptor based on contour information
Sarmiento, N. R., Delrieux, C., & Gonzaléz-José, R. (2016)
Form and shape descriptors are among the most useful features for object identification and recognition. Even though there exists a widely used set of shape descriptors and underlying computational methods for their evaluation, frequently they fail to distinguish among very similar objects that they appear very different to the human eye. The authors propose a new set of shape descriptors based on a finer determination of the object symmetry axes, and a more accurate estimation of the bilateral and radial symmetries. These descriptors were thoroughly tested using several synthetic and real objects with varying degrees of symmetry. The methods for axes estimation and symmetry descriptors extraction outperform the widespread shape descriptors in recognising and identifying among very similar objects.
object symmetry axes determination; contour information; radial symmetry shape descriptor
Publicado en: IET Biometrics
Automatic ear detection and feature extraction using Geometric Morphometrics and Convolutional Neural Networks
Cintas, C., Quinto-Sánchez, M., Acuña, V., Paschetta, C., De Azevedo, S., de Cerqueira, C. S., ... & Canizales-Quinteros, S. (2016)
Accurate gathering of phenotypic information is a key aspect in several subject matters, including biometrics, biomedical analysis, forensics, and many other. Automatic identification of anatomical structures of biometric interest, such as fingerprints, iris patterns, or facial traits, are extensively used in applications like access control and anthropological research, all having in common the drawback of requiring intrusive means for acquiring the required information. In this regard, the ear structure has multiple advantages. Not only the ear's biometric markers can be easily captured from the distance with non intrusive methods, but also they experiment almost no changes over time, and are not influenced by facial expressions. Here we present a new method based on Geometric Morphometrics and Deep Learning for automatic ear detection and feature extraction in the form of landmarks. A convolutional neural network was trained with a set of manually landmarked examples. The network is able to provide morphometric landmarks on ears' images automatically, with a performance that matches human landmarking. The feasibility of using ear landmarks as feature vectors opens a novel spectrum of biometrics applications.
image matching; feature extraction; computational geometry; neural nets; learning (artificial intelligence);biometrics (access control)
Publicado en: Computer Animation and Virtual Worlds
Realistic modeling of porous materials
Baravalle, R., Scandolo, L., Delrieux, C., García Bauza, C., & Eisemann, E. (2016)
Photorealistic modeling and rendering of materials with complex internal mesostructure is a hard challenge in Computer Graphics. In particular, macroscopic porous materials consist of complex translucent substances that exhibit different details and light interaction at several different scales. State-of-the-art techniques for modeling porous materials manage the material either as a surface and set up complex capture procedures or as a volume by employing different instances of procedural noise models for its representation. While the surface solution achieves several desired material properties, it still presents drawbacks in practical applications—high computational costs, complex capture procedures, and poor image variability, among others. Volumetric solutions are more flexible, but the final structure and appearance are difficult to control. To overcome these drawbacks, we propose an algorithm for the procedural generation of porous materials. The method is based on an artistic and physically inspired simulation of the growth of self-avoiding bubbles inside a volume, by means of dynamical systems. The patterns induced by the bubbles can be easily and intuitively controlled. The bubbles adapt to any given shape and have convincing global and local fluid-like patterns as seen in bread and sponges. Our method generates 3D textures that adequately represent porous materials, which can be used as input for creating realistic renderings of different porous objects. As a case study, we present the results of using these 3D textures as input to a direct volume renderer and show that they compare favorably with standard 3D texture synthesis methods. Copyright © 2016 John Wiley & Sons, Ltd.
porous materials;dynamical systems;photorealism