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2021 Report Closed Access

Using random forests to classify vessels from naive geometrical features
Salerno E.
This report is concerned with the application of Random Forest classification methods to the identification of ship types in moderate-resolution SAR images. After a brief presentation of the theory and and the features of this class of methods, we select an R package useful to train, test and execute the classifier. Some experiments are then reported using naive geometrical features extracted from a few thousands of targets in the OpenSARShip data set. All the ship chips extracted are derived from IW GRD Sentinel 1 C-band SAR images, accompanied by AIS and MarineTraffic ground-truth data. The ideal performance of this classifier is evaluated through the standard classification indices, with respect to the ship types that are sufficiently represented in the subsets considered.Source: ISTI Working papers, 2021

See at: CNR ExploRA Restricted


2021 Report Closed Access

Naive bayes for naive geometry: classifying vessels from length and beam
Salerno E.
This report is concerned with the application of a Naive Bayes classification method to the identification of ship types in moderate-resolution SAR images. After a brief presentation of the principles behind the method, a simple implementation and an extensive experimentation on naive geometrical features extracted from a few thousands of targets in the OpenSARShip data set are presented. All the ship chips extracted are derived from IW GRD Sentinel 1 C-band SAR images, accompanied by AIS and MarineTraffic ground-truth data. The ideal performance of this Naive Bayes is evaluated through the standard classification indices, with respect to the ship types that are sufficiently represented in the subsets considered.Source: ISTI Working papers, 2021

See at: CNR ExploRA Restricted


2021 Journal article Open Access OPEN

Analysis of diagnostic images of artworks and feature extraction: design of a methodology
Amura A., Aldini A., Pagnotta S., Salerno E., Tonazzini A., Triolo P.
Digital images represent the primary tool for diagnostics and documentation of the state of preservation of artifacts. Today the interpretive filters that allow one to characterize information and communicate it are extremely subjective. Our research goal is to study a quantitative analysis methodology to facilitate and semi-automate the recognition and polygonization of areas corresponding to the characteristics searched. To this end, several algorithms have been tested that allow for separating the characteristics and creating binary masks to be statistically analyzed and polygonized. Since our methodology aims to offer a conservator-restorer model to obtain useful graphic documentation in a short time that is usable for design and statistical purposes, this process has been implemented in a single Geographic Information Systems (GIS) application.Source: JOURNAL OF IMAGING 7 (2021). doi:10.3390/jimaging7030053
DOI: 10.3390/jimaging7030053

See at: ISTI Repository Open Access | CNR ExploRA Open Access | DOAJ-Articles Open Access | Journal of Imaging Open Access


2021 Journal article Open Access OPEN

Integration of multiple resolution data in 3D chromatin reconstruction using ChromStruct
Caudai C., Zoppè M., Tonazzini A., Merelli I., Salerno E.
The three-dimensional structure of chromatin in the cellular nucleus carries important information that is connected to physiological and pathological correlates and dysfunctional cell behaviour. As direct observation is not feasible at present, on one side, several experimental techniques have been developed to provide information on the spatial organization of the DNA in the cell; on the other side, several computational methods have been developed to elaborate experimental data and infer 3D chromatin conformations. The most relevant experimental methods are Chromosome Conformation Capture and its derivatives, chromatin immunoprecipitation and sequencing techniques (CHIP-seq), RNA-seq, fluorescence in situ hybridization (FISH) and other genetic and biochemical techniques. All of them provide important and complementary information that relate to the three-dimensional organization of chromatin. However, these techniques employ very different experimental protocols and provide information that is not easily integrated, due to different contexts and different resolutions. Here, we present an open-source tool, which is an expansion of the previously reported code ChromStruct, for inferring the 3D structure of chromatin that, by exploiting a multilevel approach, allows an easy integration of information derived from different experimental protocols and referred to different resolution levels of the structure, from a few kilobases up to Megabases. Our results show that the introduction of chromatin modelling features related to CTCF CHIA-PET data, histone modification CHIP-seq, and RNA-seq data produce appreciable improvements in ChromStruct's 3D reconstructions, compared to the use of HI-C data alone, at a local level and at a very high resolution.Source: Biology (Basel) 10 (2021): 338. doi:10.3390/biology10040338
DOI: 10.3390/biology10040338

See at: Europe PubMed Central Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | www.mdpi.com Open Access | Biology Open Access


2021 Report Closed Access

Multiple kernel learning to classify vessels from naive geometrical features
Salerno E.
This report is concerned with the application of a Multiple Kernel Learning classification method to the identification of ship types in moderate-resolution SAR images. After a brief presentation of the theory and and the features of this class of methods, we select a few R packages useful to this aim, and delineate a procedure to select the relevant features and kernel functions, execute and test the classifier. Some experiments are then reported using naive geometrical features extracted from a few thousands of targets in the OpenSARShip data set. All the ship chips extracted are derived from IW GRD Sentinel 1 C-band SAR images, accompanied by AIS and MarineTraffic ground-truth data. The ideal performance of this classifier is evaluated through the standard classification indices, with respect to the ship types that are sufficiently represented in the subsets considered.Source: ISTI Working papers, 2021

See at: CNR ExploRA Restricted


2021 Report Open Access OPEN

SI-Lab Annual Research Report 2020
Leone G. R., Righi M., Carboni A., Caudai C., Colantonio S., Kuruoglu E. E., Leporini B., Magrini M., Paradisi P., Pascali M. A., Pieri G., Reggiannini M., Salerno E., Scozzari A., Tonazzini A., Fusco G., Galesi G., Martinelli M., Pardini F., Tampucci M., Buongiorno R., Bruno A., Germanese D., Matarese F., Coscetti S., Coltelli P., Jalil B., Benassi A., Bertini G., Salvetti O., Moroni D.
The Signal & Images Laboratory (http://si.isti.cnr.it/) is an interdisciplinary research group in computer vision, signal analysis, smart vision systems and multimedia data understanding. It is part of the Institute for Information Science and Technologies of the National Research Council of Italy. This report accounts for the research activities of the Signal and Images Laboratory of the Institute of Information Science and Technologies during the year 2020.Source: ISTI Technical Report, ISTI-2021-TR/009, pp.1–38, 2021
DOI: 10.32079/isti-tr-2021/009

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2021 Report Closed Access

OSIRIS-FO - OSIRIS PDR Meeting - CNR-ISTI current status
Salerno E., Martinelli M., Reggiannini M., Righi M., Tampucci M.
ESA OSIRIS 2 Project - Current status of CNR-ISTISource: ISTI Project report, OSIRIS-FO, 2021

See at: CNR ExploRA Restricted


2020 Report Closed Access

Uso di tecniche di sparse independent component analysis per l'estrazione di regioni di interesse in opere pittoriche e grafiche
Salerno E.
In questa nota si mostra come, in certe applicazioni legate alle tecnologie dell'informazione per lo studio del patrimonio culturale, possano essere applicati metodi di separazione cieca delle componenti basati sulla sparsità e non sull'indipendenza statistica. Nelle applicazioni in cui sia necessario estrarre da immagini di opere pittoriche o manoscritti delle regioni di interesse isolate spazialmente, le condizioni di sparsità sono teoricamente verificate già nello spazio delle immagini, e non occorre passare a uno spazio trasformato per poterle imporre alla soluzione del problema. Da due algoritmi recentemente proposti in letteratura, sono stati derivati e sperimentati i corrispondenti operanti direttamente nello spazio delle immagini. Uno di essi impone solo il requisito di sparsità, mentre l'altro aggiunge anche un vincolo di incorrelazione. Gli esperimenti sono condotti su due immagini reali, una relativa a un dipinto acquisito nel visibile e nell'infrarosso e una a un manoscritto acquisito su entrambe le facce nelle tre bande rossa, verde e blu dello spettro visibile.Source: ISTI Working papers, 2020

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2020 Report Closed Access

Integration of analysis of the hierarchical process and dempster-shafer theory for cooperative evaluation tasks
Salerno E.
This note gives some details on the application of Saaty's Analysis of Hierarchy Process and the Dempster-Shafer theory for an evaluation problem that embeds a multicriterion decision and an expert judgement on a number of value indicators. These two tasks are assumed to be entitled to two groups of experts. The judgement matrices issued by the first group are geometrically averaged and the related criteria are prioritized by the analysis of hierarchy process. Then, the judgements from the second group of experts are translated into a fuzzy language and fused through the Dempster-Shafer theory. Finally, the masses resulting from this process are propagated up the hierarchy using the previously computed priorities.Source: ISTI Working papers, 2020

See at: CNR ExploRA Restricted


2020 Report Closed Access

Sensitivity analysis to plan meliorative actions on a cultural heritage asset evaluated through a multicriteria decision making method
Salerno E.
This paper proposes a strategy to increase the value of any asset relevant to cultural heritage, measured through a multicriteria decision making method. The value of any object can be defined on the basis of its fitness to fulfil specified objectives, its significance to the people who own or use it, its potential to produce revenues, and a host of additional criteria depending on its nature. The multiple criteria on which the analysis is based are often of subjective nature, relying on judgements issued by several experts, stakeholders and decision makers. It is thus important to assess the sensitivity of the result to possible perturbations of the data. Here we propose to exploit the sensitivity analysis to identify a set of suitable lines of intervention to improve the value of the asset.Source: ISTI Working papers, 2020

See at: CNR ExploRA Restricted


2020 Journal article Open Access OPEN

Color segmentation and neural networks for automatic graphic relief of the state of conservation of artworks
Amura A., Tonazzini A., Salerno E., Pagnotta S., Palleschi V.
This paper proposes a semi-automated methodology based on a sequence of analysis processes performed on multispectral images of artworks and aimed at the extraction of vector maps regarding their state of conservation. The graphic relief of the artwork represents the main instrument of communication and synthesis of information and data acquired on cultural heritage during restoration. Despite the widespread use of informatics tools, currently, these operations are still extremely subjective and require high execution times and costs. In some cases, manual execution is particularly complicated and almost impossible to carry out. The methodology proposed here allows supervised, partial automation of these procedures avoids approximations and drastically reduces the work times, as it makes a vector drawing by extracting the areas directly from the raster images. We propose a procedure for color segmentation based on principal/independent component analysis (PCA/ICA) and SOM neural networks and, as a case study, present the results obtained on a set of multispectral reproductions of a painting on canvas.Source: Cultura e scienza del colore 12 (2020): 7–15. doi:10.23738/CCSJ.120201
DOI: 10.23738/ccsj.120201

See at: jcolore.gruppodelcolore.it Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2020 Report Closed Access

Optical/SAR data and system Integration for Rush Identification of Ship models OSIRIS 2 - ESA Project The Ground Truth Data Base
Martinelli M., Reggiannini M., Righi M., Salerno E., Tampucci M.
Presentazione Kick-Off MeetingSource: Project report, 2020

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2020 Report Closed Access

OSIRIS-FO
Martinelli M., Moroni D., Reggiannini M., Righi M., Salerno E., Tampucci M.
OSIRIS-FO Ship Classification and Ship Kinematics EstimationSource: Project report, OSIRIS-FO, 2020

See at: CNR ExploRA Restricted


2020 Journal article Open Access OPEN

Identifying Value-Increasing Actions for Cultural Heritage Assets through Sensitivity Analysis of Multicriteria Evaluation Results
Salerno E.
This paper presents a brief overview of multicriteria decision making (MCDM) as applied to the evaluation of adaptive reuse projects for cultural heritage assets and proposes a strategy to plan interventions to increase their value. The value of an object can be defined from its fitness to fulfil specified objectives, its significance to the people who own or use it, its potential to produce revenues, and a host of other criteria depending on its nature. These criteria are often subjective, relying on judgements issued by several experts, stakeholders and decision makers. This is why the MCDM methods need to formalize the problem so as to make it suitable to be treated quantitatively. Moreover, its sensitivity to variable opinions must be studied to check the stability of the result. We propose to leverage sensitivity analysis to identify the lines of intervention that promise to be the most effective to increase the value of the asset. A simulated example illustrates this strategy. This approach promises to be useful when assessing the sustainability of a reuse or redevelopment project in the cases where the final destination of the asset is still under examination.Source: Sustainability (Basel) 12 (2020). doi:10.3390/su12219238
DOI: 10.3390/su12219238

See at: Sustainability Open Access | Sustainability Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | Sustainability Open Access | Sustainability Open Access


2019 Journal article Open Access OPEN

Estimation of the spatial chromatin structure based on a multiresolution bead-chain model
Caudai C., Salerno E., Zoppe M., Tonazzini A.
We present a method to infer 3D chromatin configurations from Chromosome Conformation Capture data. Quite a few methods have been proposed to estimate the structure of the nuclear DNA in homogeneous populations of cells from this kind of data. Many of them transform contact frequencies into Euclidean distances between pairs of chromatin fragments, and then reconstruct the structure by solving a distance-to-geometry problem. To avoid inconsistencies, our method is based on a score function that does not require any frequency-to-distance translation. We propose a multiscale chromatin model where the chromatin fibre is suitably partitioned at each scale. The partial structures are estimated independently, and connected to rebuild the whole fibre. Our score function consists in a data-fit part and a penalty part, balanced automatically at each scale and each subchain. The penalty part enforces "soft" geometric constraints. As many different structures can fit the data, our sampling strategy produces a set of solutions with similar scores. The procedure contains a few parameters, independent of both the scale and the genomic segment treated. The partition of the fibre, along with intrinsically parallel parts, make this method computationally efficient. Results from human genome data support the biological plausibility of our solutions.Source: IEEE/ACM transactions on computational biology and bioinformatics (Print) 16 (2019): 550–559. doi:10.1109/TCBB.2018.2791439
DOI: 10.1109/tcbb.2018.2791439

See at: ISTI Repository Open Access | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | CNR ExploRA Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted


2019 Journal article Open Access OPEN

ChromStruct 4: a Python code to estimate the chromatin structure from Hi-C data
Caudai C., Salerno E., Zoppè M., Merelli I., Tonazzini A.
A method and a stand-alone Python(TM) code to estimate the 3D chromatin structure from chromosome conformation capture data are presented. The method is based on a multiresolution, modified-bead-chain chromatin model, evolved through quaternion operators in a Monte Carlo sampling. The solution space to be sampled is generated by a score function with a data-fit part and a constraint part where the available prior knowledge is implicitly coded. The final solution is a set of 3D configurations that are compatible with both the data and the prior knowledge. The iterative code, provided here as additional material, is equipped with a graphical user interface and stores its results in standard-format files for 3D visualization. We describe the mathematical-computational aspects of the method and explain the details of the code. Some experimental results are reported, with a demonstration of their fit to the data.Source: IEEE/ACM transactions on computational biology and bioinformatics (Online) 16 (2019): 1867–1878. doi:10.1109/TCBB.2018.2838669
DOI: 10.1109/tcbb.2018.2838669

See at: ISTI Repository Open Access | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | ieeexplore.ieee.org Restricted | CNR ExploRA Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted | IEEE/ACM Transactions on Computational Biology and Bioinformatics Restricted


2019 Journal article Open Access OPEN

A new infrared true-color approach for visible-infrared multispectral image analysis
Grifoni E., Campanella B., Legnaioli S., Lorenzetti G., Marras L., Pagnotta S., Palleschi V., Poggialini F., Salerno E., Tonazzini A.
In this article, we present a newmethod for the analysis of visible/Infraredmultispectral sets producing chromatically faithful false-color images, whichmaintain a good readability of the information contained in the non-visible Infrared band. Examples of the application of this technique are given on the multispectral images acquired on the Pietà of Santa Croce of Agnolo Bronzino (1569, Florence) and on the analysis and visualization of the multispectral data obtained on Etruscanmural paintings (Tomb of the Monkey, Siena, Italy, V century B.C.). The fidelity of the chromatic appearance of the resulting images, coupled to the effective visualization of the information contained in the Infrared band, opens interesting perspectives for the use of the method for visualization and presentation of the results of multispectral analysis in Cultural Heritage diffusion, research, and diagnostics.Source: ACM journal on computing and cultural heritage (Print) 12 (2019): 8:1–8:11. doi:10.1145/3241065
DOI: 10.1145/3241065

See at: ISTI Repository Open Access | Journal on Computing and Cultural Heritage Restricted | Journal on Computing and Cultural Heritage Restricted | dl.acm.org Restricted | Journal on Computing and Cultural Heritage Restricted | Journal on Computing and Cultural Heritage Restricted | Journal on Computing and Cultural Heritage Restricted | CNR ExploRA Restricted


2019 Journal article Open Access OPEN

Analytical and mathematical methods for revealing hidden details in ancient manuscripts and paintings: A review
Tonazzini A., Salerno E., Abdel-salam Z. A., Harith M. A., Marras L., Botto A., Campanella B., Legnaioli S., Pagnotta S., Poggialini F., Palleschi V.
In this work, a critical review of the current nondestructive probing and image analysis approaches is presented, to revealing otherwise invisible or hardly discernible details in manuscripts and paintings relevant to cultural heritage and archaeology. Multispectral imaging, X-ray fluorescence, Laser-Induced Breakdown Spectroscopy, Raman spectroscopy and Thermography are considered, as techniques for acquiring images and spectral image sets; statistical methods for the analysis of these images are then discussed, including blind separation and false colour techniques. Several case studies are presented, with particular attention dedicated to the approaches that appear most promising for future applications. Some of the techniques described herein are likely to replace, in the near future, classical digital photography in the study of ancient manuscripts and paintings. (C) 2019 The Authors. Published by Elsevier B.V.Source: Journal of Advanced Research (Print) (Print) 17 (2019): 31–42. doi:10.1016/j.jare.2019.01.003
DOI: 10.1016/j.jare.2019.01.003

See at: Journal of Advanced Research Open Access | Journal of Advanced Research Open Access | Journal of Advanced Research Open Access | Journal of Advanced Research Open Access | europepmc.org Open Access | Europe PubMed Central Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | Journal of Advanced Research Open Access | Journal of Advanced Research Open Access | Journal of Advanced Research Open Access | Journal of Advanced Research Open Access


2019 Journal article Open Access OPEN

Remote sensing for maritime prompt monitoring
Reggiannini M., Righi M., Tampucci M., Lo Duca A., Bacciu C., Bedini L., D'Errico A., Di Paola C., Marchetti A., Martinelli M., Mercurio C., Salerno E., Zizi B.
The main purpose of this paper is to describe a software platform dedicated to sea surveillance, capable of detecting and identifying illegal maritime traffic. This platform results from the cascade pipeline of several image processing algorithms that input Radar or Optical imagery captured by satellite-borne sensors and try to identify vessel targets in the scene and provide quantitative descriptors about their shape and motion. This platform is innovative since it integrates in its architecture heterogeneous data and data processing solutions with the goal of identifying navigating vessels in a unique and completely automatic processing streamline. More in detail, the processing chain consists of: (i) the detection of target vessels in an input map; (ii) the estimation of each vessel's most descriptive geometrical and scatterometric (for radar images) features; (iii) the estimation of the kinematics of each vessel; (iv) the prediction of each vessel's forthcoming route; and (v) the visualization of the results in a dedicated webGIS interface. The resulting platform represents a novel tool to counteract unauthorized fishing and tackle irregular migration and the related smuggling activities.Source: Journal of marine science and engineering 7 (2019). doi:10.3390/jmse7070202
DOI: 10.3390/jmse7070202

See at: Journal of Marine Science and Engineering Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | Journal of Marine Science and Engineering Open Access | Journal of Marine Science and Engineering Open Access


2019 Journal article Open Access OPEN

Virtual restoration and content analysis of ancient degraded manuscripts
Tonazzini A., Savino P., Salerno E., Hanif M., Debole F.
In recent years, extensive campaigns of digitization of the documental heritage conserved in libraries and archives have been performed, with the primary goal to ensure the preservation and fruition of this important part of the human cultural and historical patrimony. Besides protecting conservation, the availability of high quality digital copies has increasingly stimulated the use of image processing techniques, to perform a number of operations on documents and manuscripts, without harming the often precious and fragile originals. Among those, virtual restoration tasks are crucial, as they facilitate the traditional work of philologists and paleographers, and constitute a first step towards an automatic analysis of the written contents. Here we report our experience in this field, referring, as a case study, to the problem of removing one of the most frequent and impairing degradations affecting ancient manuscripts, i.e., the bleed-through distortion.We show that techniques of blind source separation are versatile tools to either cancel these unwanted interferences or isolate specific features for content analysis goals. Specialized algorithms, based on recto-verso models and sparse image representation, are then shown to be able to perform a fine and selective removal of the degradation, while preserving the original appearance of the manuscript.Source: International Journal of Information Science and Technology 3 (2019): 16–25.

See at: ISTI Repository Open Access | CNR ExploRA Open Access | www.innove.org Open Access