Francescomaria Marino - Academia.edu (original) (raw)

Papers by Francescomaria Marino

Research paper thumbnail of F. MARINO, A. DISTANTE, P.L. MAZZEO and E. STELLA: A Real Time Visual Inspection System... A Real Time Visual Inspection System for Railway Maintenance: Automatic Hexagonal Headed Bolts Detection

Abstract—Rail inspection is a very important task in railway maintenance and it is periodically n... more Abstract—Rail inspection is a very important task in railway maintenance and it is periodically needed for preventing dangerous situations. Inspection is operated manually by trained human operator walking along the track searching for visual anomalies. This monitoring is unacceptable for slowness and lack of objectivity, because the results are related to the ability of the observer to recognize critical situations. The paper presents VISyR, a patent pending real time Visual Inspection System for Railway maintenance, and describes how presence/absence of the fastening bolts that fix the rails to the sleepers is automatically detected. VISyR acquires images from a digital line scan camera. Data are simultaneously preprocessed according to two Discrete Wavelet Transforms, and then provided to two Multi Layer Perceptron Neural Classifiers (MLPNCs). The “cross validation ” of these MLPNCs avoids (practically-at-all) false positive, and reveals the presence/absence of the fastening bolt...

Research paper thumbnail of 8 ViSyR : a Vi sion Sy stem for R eal-Time Infrastructure Inspection

The railway maintenance is a particular application context in which the periodical surface inspe... more The railway maintenance is a particular application context in which the periodical surface inspection of the rolling plane is required in order to prevent any dangerous situation. Usually, this task is performed by trained personnel that, periodically, walks along the railway network searching for visual anomalies. Actually, this manual inspection is slow, laborious and potentially hazardous, and the results are strictly dependent on the capability of the observer to detect possible anomalies and to recognize critical situations. With the growing of the high-speed railway traffic, companies over the world are interested to develop automatic inspection systems which are able to detect rail defects, sleepers’ anomalies, as well as missing fastening elements. These systems could increase the ability in the detection of defects and reduce the inspection time in order to guarantee more frequently the maintenance of the railway network. This book chapter presents ViSyR: a patented fully ...

Research paper thumbnail of Real-time algorithms and architecture for coding with a dwt-based methods compressed images

Research paper thumbnail of DUBIO: A Fully Automatic Drones Cloud Based Infrared Monitoring System for Large-Scale PV Plants

2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2018

Research paper thumbnail of A Tversky Loss-Based Convolutional Neural Network for Liver Vessels Segmentation

Intelligent Computing Theories and Application, 2020

Research paper thumbnail of Unmanned Aerial Vehicle-Based Non Destructive Diagnostics

2018 IEEE 4th International Forum on Research and Technology for Society and Industry (RTSI), 2018

Responsive microgels based on poly(N-isopropylacrylamide) (PNIPAM) exhibit peculiar behaviours du... more Responsive microgels based on poly(N-isopropylacrylamide) (PNIPAM) exhibit peculiar behaviours due to the competition between the hydrophilic and hydrophobic interactions of the constituent networks. The interpenetration of poly-acrilic acid (PAAc), a pH-sensitive polymer, within the PNIPAM network, to form Interpenetrated Polymer Network (IPN) microgels, affects this delicate balance and the typical Volume-Phase Transition (VPT) leading to complex behaviours whose molecular nature is still completely unexplored. Here we investigate the molecular mechanism driving the VPT and its influence on particle aggregation for PNIPAM/PAAc IPN microgels by the joint use of Dynamic Light Scattering and Raman Spectroscopy. Our results highlight that PNIPAM hydrophobicity is enhanced by the interpenetration of PAAc promoting interparticle interactions, a crossover concentration is found above which aggregation phenomena become relevant. Moreover we find that, at variance with PNIPAM, for IPN microgels a double-step molecular mechanisms occurs upon crossing the VPT, the first involving the coil-to-globule transition typical of PNIPAM and the latter associated to PAAc steric hindrance.

Research paper thumbnail of Semantic Segmentation Framework for Glomeruli Detection and Classification in Kidney Histological Sections

Electronics, 2020

The evaluation of kidney biopsies performed by expert pathologists is a crucial process for asses... more The evaluation of kidney biopsies performed by expert pathologists is a crucial process for assessing if a kidney is eligible for transplantation. In this evaluation process, an important step consists of the quantification of global glomerulosclerosis, which is the ratio between sclerotic glomeruli and the overall number of glomeruli. Since there is a shortage of organs available for transplantation, a quick and accurate assessment of global glomerulosclerosis is essential for retaining the largest number of eligible kidneys. In the present paper, the authors introduce a Computer-Aided Diagnosis (CAD) system to assess global glomerulosclerosis. The proposed tool is based on Convolutional Neural Networks (CNNs). In particular, the authors considered approaches based on Semantic Segmentation networks, such as SegNet and DeepLab v3+. The dataset has been provided by the Department of Emergency and Organ Transplantations (DETO) of Bari University Hospital, and it is composed of 26 kidn...

Research paper thumbnail of Wavelet-based perceptually lossless coding of R-G-B images

Integrated Computer-Aided Engineering, 2000

ABSTRACT A perceptually-lossless wavelet-based image compression algorithm and architecture worki... more ABSTRACT A perceptually-lossless wavelet-based image compression algorithm and architecture working directly in the R-G-B color domain is proposed. Even though the highest compression ratios are achievable in the Luminance-Chrominance domain, image sensors generate data commonly in a subsampled R-G-B format. Many real-time applications (e.g., a low cost digital camera) prohibit the on-line conversion of data from R-G-B format to any other format. Therefore, in these applications, it is desirable to apply the compression directly on R-G-B data. Our compression scheme is based on derived perceptually-lossless quantizing thresholds, and can be mapped into an ASIC yielding very high throughput. Examples illustrating the performance of the coder are presented.

Research paper thumbnail of A Deep Learning Approach for Hepatocellular Carcinoma Grading

International Journal of Computer Vision and Image Processing, 2017

Introduction and objective: Computer Aided Decision (CAD) systems based on Medical Imaging could ... more Introduction and objective: Computer Aided Decision (CAD) systems based on Medical Imaging could support radiologists in grading Hepatocellular carcinoma (HCC) by means of Computed Tomography (CT) images, thus avoiding medical invasive procedures such as biopsies. The identification and characterization of Regions of Interest (ROIs) containing lesions is an important phase allowing an easier classification in two classes of HCCs. Two steps are needed for the detection of lesioned ROIs: a liver isolation in each CT slice and a lesion segmentation. Materials and methods: Materials consist in abdominal CT hepatic lesion from 18 patients subjected to liver transplant, partial hepatectomy, or US-guided needle biopsy. Several approaches are implemented to segment the region of liver and, then, detect the lesion ROI. Results: A Deep Learning approach using Convolutional Neural Network is followed for HCC grading. The obtained good results confirm the robustness of the segmentation algorith...

Research paper thumbnail of Synthesis of a Neural Network Classifier for Hepatocellular Carcinoma Grading Based on Triphasic CT Images

Communications in Computer and Information Science, 2017

Computer Aided Decision (CAD) systems based on Medical Imaging could support radiologists in grad... more Computer Aided Decision (CAD) systems based on Medical Imaging could support radiologists in grading Hepatocellular carcinoma (HCC) by means of Computed Tomography (CT) images, avoiding that patient undergo any medical invasive procedures such as biopsies. The individuation and characterization of Regions of Interest (ROIs) containing lesions is an important phase that enables an easier classification between two classes of HCCs. Two phases are needed for the individuation of lesioned ROIs: a liver isolation in each CT slice, and a lesion segmentation. Ultimately, all individuated ROIs are described by morphological features and, finally, a feed-forward supervised Artificial Neural Network (ANN) is used to classify them. Testing determined that the ANN topologies found through an evolutionary strategy showed a high generalization on the mean performance indices regardless of applied training, validation and test sets, showing good performances in terms of both accuracy and sensitivity, permitting a correct grading of HCC lesions.

Research paper thumbnail of A Quantitative and Computer-Aided Thermography-Based Diagnostics for PV Devices—Part II: Platform and Results

IEEE Journal of Photovoltaics, 2017

This paper, Part II, deals with the software platform that implements the workflow described in P... more This paper, Part II, deals with the software platform that implements the workflow described in Part I, i.e., a thermography-based diagnostics able to provide a detailed, clear, and unambiguous information on the health state of photovoltaic (PV) modules. The methodology, in fact, allows a numerical and qualitative evaluation of each cell of the PV module. In particular, this paper deeply describes the main features of the software platform and introduces the graphical user interface that makes the framework efficiently and effectively adoptable since it leads to the automatic generation of a report. In order to show the manifold features, three cases of study, which have been derived from a real monitoring survey, are discussed, highlighting the critical situations revealed neither with a direct observation of the infrared image nor with its manual processing: The first case in regard to a defected PV module and the second one an almost completely uniform module, while the third one deals with a dishomogeneous module.

Research paper thumbnail of A novel approach to evaluate blood parameters using computer vision techniques

2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA), 2016

Research paper thumbnail of Computer Assisted Detection of Breast Lesions in Magnetic Resonance Images

Lecture Notes in Computer Science, 2016

Nowadays preventive screening policies and increased awareness initiatives are up surging the wor... more Nowadays preventive screening policies and increased awareness initiatives are up surging the workload of radiologists. Due to the growing number of women undergoing first-level screening tests, systems that can make these operations faster and more effective are required. This paper presents a Computer Assisted Detection system based on medical imaging techniques and capable of labeling potentially cancerous breast lesions. This work is based on MRIs performed with morphological and dynamic sequences, obtained and classified thanks to the collaboration of the specialists from the University of Bari Aldo Moro (Italy). A first set of 60 images was acquired without Contrast Method for each patient and, subsequently, 100 more slices were taken with Contrast Method. This article formally describes the techniques adopted to segment these images and extract the most significant features from each Region of Interest (ROI). Then, the underlying architecture of the suggested Artificial Neural Network (ANN) responsible of identifying suspect lesions will be presented. We will discuss the architecture of the supervised neural network based on the algorithm named Robust Error Back Propagation, trained and optimized so to maximize the number of True Positive ROIs, i.e., the actual tumor regions. The training set, built with physicians’ help, consists of 94 lesions and 3700 regions of any interest extracted with the proposed segmentation technique. Performances of the ANN, trained using 60 % of the samples, are evaluated in terms of accuracy, sensitivity and specificity indices. In conclusion, these tests show that a supervised machine learning approach to the detection of breast lesions in Magnetic Resonance Images is consistent, and shows good performance, especially from a False Negative reduction perspective.

Research paper thumbnail of Design of a Projective AR Workbench for Manual Working Stations

Lecture Notes in Computer Science, 2016

We present the design and a prototype of a projective AR workbench for an effective use of the AR... more We present the design and a prototype of a projective AR workbench for an effective use of the AR in industrial applications, in particular for Manual Working Stations. The proposed solution consists of an aluminum structure that holds a projector and a camera that is intended to be mounted on manual working stations. The camera, using a tracking algorithm, computes in real time the position and orientation of the object while the projector displays the information always in the desired position. We also designed and implemented the data structure of a database for the managing of AR instructions, and we were able to access this information interactively from our application.

Research paper thumbnail of On the Steganography Effects in Digital Images

In this paper the effects of steganography in different image formats (BMP, GIF, JPEG and DWT-cod... more In this paper the effects of steganography in different image formats (BMP, GIF, JPEG and DWT-coded) are studied. With respect to these formats, we try to give an answer to the following questions: "how many bits of noise (i.e. the textual secret message) can be injected without perceptually deteriorating the quality of the image?" and "how and where to inject these bits in order to achieve the best trade-off in terms of length of the textual message and preserved quality of the image?".

Research paper thumbnail of A GUI based analysis of infrared images of PV modules

2015 International Conference on Clean Electrical Power (ICCEP), 2015

ABSTRACT

Research paper thumbnail of Multi Channel Shared-Memory Device for Parallel Processing

Applied Informatics, 1994

Research paper thumbnail of A fixed-point parallel convolver without precision loss for the real-time processing of long numerical sequences

Parallel and Distributed Processing, International Symposium, 1995

A parallel architecture, able to convolve in real-time long numerical sequences with long filter ... more A parallel architecture, able to convolve in real-time long numerical sequences with long filter functions is shown. Real-time is intended as a processing made at the same frequency of the data input access with a minimum delay of the output production, in order to make the output immediately available during the input process. We have used a known scheme that

Research paper thumbnail of Steganography effects in various formats of images. A preliminary study

IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2001

In this paper, the effects of steganography in different image formats (BMP, GIF, JPEG and DWT co... more In this paper, the effects of steganography in different image formats (BMP, GIF, JPEG and DWT coded) are studied. With respect to these formats, we try to give an answer to the following questions. (1) How many bits of noise (i.e. the textual secret message) can be injected without perceptually deteriorating the quality of the image? (2) How and where

Research paper thumbnail of A GPU-based vision system for real time detection of fastening elements in railway inspection

2009 16th IEEE International Conference on Image Processing (ICIP), 2009

... P. De Ruvo1, A. Distante1, E. Stella1, and F. Marino2 1 Istituto di Studi sui Sistemi Intelli... more ... P. De Ruvo1, A. Distante1, E. Stella1, and F. Marino2 1 Istituto di Studi sui Sistemi Intelligenti per l'Automazione (ISSIA) CNR, ITALY 2 Dipartimento di Elettrotecnica ed Elettronica (DEE), Politecnico di Bari, ITALY ABSTRACT ...

Research paper thumbnail of F. MARINO, A. DISTANTE, P.L. MAZZEO and E. STELLA: A Real Time Visual Inspection System... A Real Time Visual Inspection System for Railway Maintenance: Automatic Hexagonal Headed Bolts Detection

Abstract—Rail inspection is a very important task in railway maintenance and it is periodically n... more Abstract—Rail inspection is a very important task in railway maintenance and it is periodically needed for preventing dangerous situations. Inspection is operated manually by trained human operator walking along the track searching for visual anomalies. This monitoring is unacceptable for slowness and lack of objectivity, because the results are related to the ability of the observer to recognize critical situations. The paper presents VISyR, a patent pending real time Visual Inspection System for Railway maintenance, and describes how presence/absence of the fastening bolts that fix the rails to the sleepers is automatically detected. VISyR acquires images from a digital line scan camera. Data are simultaneously preprocessed according to two Discrete Wavelet Transforms, and then provided to two Multi Layer Perceptron Neural Classifiers (MLPNCs). The “cross validation ” of these MLPNCs avoids (practically-at-all) false positive, and reveals the presence/absence of the fastening bolt...

Research paper thumbnail of 8 ViSyR : a Vi sion Sy stem for R eal-Time Infrastructure Inspection

The railway maintenance is a particular application context in which the periodical surface inspe... more The railway maintenance is a particular application context in which the periodical surface inspection of the rolling plane is required in order to prevent any dangerous situation. Usually, this task is performed by trained personnel that, periodically, walks along the railway network searching for visual anomalies. Actually, this manual inspection is slow, laborious and potentially hazardous, and the results are strictly dependent on the capability of the observer to detect possible anomalies and to recognize critical situations. With the growing of the high-speed railway traffic, companies over the world are interested to develop automatic inspection systems which are able to detect rail defects, sleepers’ anomalies, as well as missing fastening elements. These systems could increase the ability in the detection of defects and reduce the inspection time in order to guarantee more frequently the maintenance of the railway network. This book chapter presents ViSyR: a patented fully ...

Research paper thumbnail of Real-time algorithms and architecture for coding with a dwt-based methods compressed images

Research paper thumbnail of DUBIO: A Fully Automatic Drones Cloud Based Infrared Monitoring System for Large-Scale PV Plants

2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2018

Research paper thumbnail of A Tversky Loss-Based Convolutional Neural Network for Liver Vessels Segmentation

Intelligent Computing Theories and Application, 2020

Research paper thumbnail of Unmanned Aerial Vehicle-Based Non Destructive Diagnostics

2018 IEEE 4th International Forum on Research and Technology for Society and Industry (RTSI), 2018

Responsive microgels based on poly(N-isopropylacrylamide) (PNIPAM) exhibit peculiar behaviours du... more Responsive microgels based on poly(N-isopropylacrylamide) (PNIPAM) exhibit peculiar behaviours due to the competition between the hydrophilic and hydrophobic interactions of the constituent networks. The interpenetration of poly-acrilic acid (PAAc), a pH-sensitive polymer, within the PNIPAM network, to form Interpenetrated Polymer Network (IPN) microgels, affects this delicate balance and the typical Volume-Phase Transition (VPT) leading to complex behaviours whose molecular nature is still completely unexplored. Here we investigate the molecular mechanism driving the VPT and its influence on particle aggregation for PNIPAM/PAAc IPN microgels by the joint use of Dynamic Light Scattering and Raman Spectroscopy. Our results highlight that PNIPAM hydrophobicity is enhanced by the interpenetration of PAAc promoting interparticle interactions, a crossover concentration is found above which aggregation phenomena become relevant. Moreover we find that, at variance with PNIPAM, for IPN microgels a double-step molecular mechanisms occurs upon crossing the VPT, the first involving the coil-to-globule transition typical of PNIPAM and the latter associated to PAAc steric hindrance.

Research paper thumbnail of Semantic Segmentation Framework for Glomeruli Detection and Classification in Kidney Histological Sections

Electronics, 2020

The evaluation of kidney biopsies performed by expert pathologists is a crucial process for asses... more The evaluation of kidney biopsies performed by expert pathologists is a crucial process for assessing if a kidney is eligible for transplantation. In this evaluation process, an important step consists of the quantification of global glomerulosclerosis, which is the ratio between sclerotic glomeruli and the overall number of glomeruli. Since there is a shortage of organs available for transplantation, a quick and accurate assessment of global glomerulosclerosis is essential for retaining the largest number of eligible kidneys. In the present paper, the authors introduce a Computer-Aided Diagnosis (CAD) system to assess global glomerulosclerosis. The proposed tool is based on Convolutional Neural Networks (CNNs). In particular, the authors considered approaches based on Semantic Segmentation networks, such as SegNet and DeepLab v3+. The dataset has been provided by the Department of Emergency and Organ Transplantations (DETO) of Bari University Hospital, and it is composed of 26 kidn...

Research paper thumbnail of Wavelet-based perceptually lossless coding of R-G-B images

Integrated Computer-Aided Engineering, 2000

ABSTRACT A perceptually-lossless wavelet-based image compression algorithm and architecture worki... more ABSTRACT A perceptually-lossless wavelet-based image compression algorithm and architecture working directly in the R-G-B color domain is proposed. Even though the highest compression ratios are achievable in the Luminance-Chrominance domain, image sensors generate data commonly in a subsampled R-G-B format. Many real-time applications (e.g., a low cost digital camera) prohibit the on-line conversion of data from R-G-B format to any other format. Therefore, in these applications, it is desirable to apply the compression directly on R-G-B data. Our compression scheme is based on derived perceptually-lossless quantizing thresholds, and can be mapped into an ASIC yielding very high throughput. Examples illustrating the performance of the coder are presented.

Research paper thumbnail of A Deep Learning Approach for Hepatocellular Carcinoma Grading

International Journal of Computer Vision and Image Processing, 2017

Introduction and objective: Computer Aided Decision (CAD) systems based on Medical Imaging could ... more Introduction and objective: Computer Aided Decision (CAD) systems based on Medical Imaging could support radiologists in grading Hepatocellular carcinoma (HCC) by means of Computed Tomography (CT) images, thus avoiding medical invasive procedures such as biopsies. The identification and characterization of Regions of Interest (ROIs) containing lesions is an important phase allowing an easier classification in two classes of HCCs. Two steps are needed for the detection of lesioned ROIs: a liver isolation in each CT slice and a lesion segmentation. Materials and methods: Materials consist in abdominal CT hepatic lesion from 18 patients subjected to liver transplant, partial hepatectomy, or US-guided needle biopsy. Several approaches are implemented to segment the region of liver and, then, detect the lesion ROI. Results: A Deep Learning approach using Convolutional Neural Network is followed for HCC grading. The obtained good results confirm the robustness of the segmentation algorith...

Research paper thumbnail of Synthesis of a Neural Network Classifier for Hepatocellular Carcinoma Grading Based on Triphasic CT Images

Communications in Computer and Information Science, 2017

Computer Aided Decision (CAD) systems based on Medical Imaging could support radiologists in grad... more Computer Aided Decision (CAD) systems based on Medical Imaging could support radiologists in grading Hepatocellular carcinoma (HCC) by means of Computed Tomography (CT) images, avoiding that patient undergo any medical invasive procedures such as biopsies. The individuation and characterization of Regions of Interest (ROIs) containing lesions is an important phase that enables an easier classification between two classes of HCCs. Two phases are needed for the individuation of lesioned ROIs: a liver isolation in each CT slice, and a lesion segmentation. Ultimately, all individuated ROIs are described by morphological features and, finally, a feed-forward supervised Artificial Neural Network (ANN) is used to classify them. Testing determined that the ANN topologies found through an evolutionary strategy showed a high generalization on the mean performance indices regardless of applied training, validation and test sets, showing good performances in terms of both accuracy and sensitivity, permitting a correct grading of HCC lesions.

Research paper thumbnail of A Quantitative and Computer-Aided Thermography-Based Diagnostics for PV Devices—Part II: Platform and Results

IEEE Journal of Photovoltaics, 2017

This paper, Part II, deals with the software platform that implements the workflow described in P... more This paper, Part II, deals with the software platform that implements the workflow described in Part I, i.e., a thermography-based diagnostics able to provide a detailed, clear, and unambiguous information on the health state of photovoltaic (PV) modules. The methodology, in fact, allows a numerical and qualitative evaluation of each cell of the PV module. In particular, this paper deeply describes the main features of the software platform and introduces the graphical user interface that makes the framework efficiently and effectively adoptable since it leads to the automatic generation of a report. In order to show the manifold features, three cases of study, which have been derived from a real monitoring survey, are discussed, highlighting the critical situations revealed neither with a direct observation of the infrared image nor with its manual processing: The first case in regard to a defected PV module and the second one an almost completely uniform module, while the third one deals with a dishomogeneous module.

Research paper thumbnail of A novel approach to evaluate blood parameters using computer vision techniques

2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA), 2016

Research paper thumbnail of Computer Assisted Detection of Breast Lesions in Magnetic Resonance Images

Lecture Notes in Computer Science, 2016

Nowadays preventive screening policies and increased awareness initiatives are up surging the wor... more Nowadays preventive screening policies and increased awareness initiatives are up surging the workload of radiologists. Due to the growing number of women undergoing first-level screening tests, systems that can make these operations faster and more effective are required. This paper presents a Computer Assisted Detection system based on medical imaging techniques and capable of labeling potentially cancerous breast lesions. This work is based on MRIs performed with morphological and dynamic sequences, obtained and classified thanks to the collaboration of the specialists from the University of Bari Aldo Moro (Italy). A first set of 60 images was acquired without Contrast Method for each patient and, subsequently, 100 more slices were taken with Contrast Method. This article formally describes the techniques adopted to segment these images and extract the most significant features from each Region of Interest (ROI). Then, the underlying architecture of the suggested Artificial Neural Network (ANN) responsible of identifying suspect lesions will be presented. We will discuss the architecture of the supervised neural network based on the algorithm named Robust Error Back Propagation, trained and optimized so to maximize the number of True Positive ROIs, i.e., the actual tumor regions. The training set, built with physicians’ help, consists of 94 lesions and 3700 regions of any interest extracted with the proposed segmentation technique. Performances of the ANN, trained using 60 % of the samples, are evaluated in terms of accuracy, sensitivity and specificity indices. In conclusion, these tests show that a supervised machine learning approach to the detection of breast lesions in Magnetic Resonance Images is consistent, and shows good performance, especially from a False Negative reduction perspective.

Research paper thumbnail of Design of a Projective AR Workbench for Manual Working Stations

Lecture Notes in Computer Science, 2016

We present the design and a prototype of a projective AR workbench for an effective use of the AR... more We present the design and a prototype of a projective AR workbench for an effective use of the AR in industrial applications, in particular for Manual Working Stations. The proposed solution consists of an aluminum structure that holds a projector and a camera that is intended to be mounted on manual working stations. The camera, using a tracking algorithm, computes in real time the position and orientation of the object while the projector displays the information always in the desired position. We also designed and implemented the data structure of a database for the managing of AR instructions, and we were able to access this information interactively from our application.

Research paper thumbnail of On the Steganography Effects in Digital Images

In this paper the effects of steganography in different image formats (BMP, GIF, JPEG and DWT-cod... more In this paper the effects of steganography in different image formats (BMP, GIF, JPEG and DWT-coded) are studied. With respect to these formats, we try to give an answer to the following questions: "how many bits of noise (i.e. the textual secret message) can be injected without perceptually deteriorating the quality of the image?" and "how and where to inject these bits in order to achieve the best trade-off in terms of length of the textual message and preserved quality of the image?".

Research paper thumbnail of A GUI based analysis of infrared images of PV modules

2015 International Conference on Clean Electrical Power (ICCEP), 2015

ABSTRACT

Research paper thumbnail of Multi Channel Shared-Memory Device for Parallel Processing

Applied Informatics, 1994

Research paper thumbnail of A fixed-point parallel convolver without precision loss for the real-time processing of long numerical sequences

Parallel and Distributed Processing, International Symposium, 1995

A parallel architecture, able to convolve in real-time long numerical sequences with long filter ... more A parallel architecture, able to convolve in real-time long numerical sequences with long filter functions is shown. Real-time is intended as a processing made at the same frequency of the data input access with a minimum delay of the output production, in order to make the output immediately available during the input process. We have used a known scheme that

Research paper thumbnail of Steganography effects in various formats of images. A preliminary study

IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2001

In this paper, the effects of steganography in different image formats (BMP, GIF, JPEG and DWT co... more In this paper, the effects of steganography in different image formats (BMP, GIF, JPEG and DWT coded) are studied. With respect to these formats, we try to give an answer to the following questions. (1) How many bits of noise (i.e. the textual secret message) can be injected without perceptually deteriorating the quality of the image? (2) How and where

Research paper thumbnail of A GPU-based vision system for real time detection of fastening elements in railway inspection

2009 16th IEEE International Conference on Image Processing (ICIP), 2009

... P. De Ruvo1, A. Distante1, E. Stella1, and F. Marino2 1 Istituto di Studi sui Sistemi Intelli... more ... P. De Ruvo1, A. Distante1, E. Stella1, and F. Marino2 1 Istituto di Studi sui Sistemi Intelligenti per l'Automazione (ISSIA) CNR, ITALY 2 Dipartimento di Elettrotecnica ed Elettronica (DEE), Politecnico di Bari, ITALY ABSTRACT ...