Amina RADGUI - Academia.edu (original) (raw)

Papers by Amina RADGUI

Proceedings of the 9th International Conference on Computer Vision Theory and Applications, 2014

The current work addresses the problem of 3D model tracking in the context of omnidirectional vis... more The current work addresses the problem of 3D model tracking in the context of omnidirectional vision in order to object tracking. However, there is few articles dealing this problem in catadioptric vision. This paper is an attempt to describe a new approach of omnidirectional images (gray level) processing based on inverse stereographic projection in the half-sphere. We used the spherical model. For object tracking, The object tracking method used is snake, with optimization using the Greedy algorithm, by adapting its different operators. This method algorithm will respect the deformed geometry of omnidirectional images such as the spherical neighbourhood, the spherical gradient and reformulation of optimization algorithm on the spherical domain. This tracking method-that we call spherical snake-permit to know the change of the shape and the size of 2D object in different replacements in the spherical image.

Computer Science Research Notes

The recent proliferation of advanced data collection technologies for Patient Generated Health Da... more The recent proliferation of advanced data collection technologies for Patient Generated Health Data (PGHD) has made remote health monitoring more accessible. However, the complex nature of the big volume of medical generated data presents a significant challenge for traditional patient monitoring approaches, impeding the effective extraction of useful information. In this context, it is imperative to develop a robust and cost-effective framework that provides the scalability and deals with the heterogeneity of PGHD in real-time. Such a system could serve as a reference and would guide future research for monitoring patient undergoing a treatment at home conditions. This study presents a real-time visual analytics framework offering insightful visual representations of the multimodal big data. The proposed system was designed following the principles of User Centered Design (UCD) to ensure that it meets the needs and expectations of medical practitioners. The usability of this framew...

Lecture notes in networks and systems, 2023

Fetal biometry (FB) and amniotic fluid volume (AFV) assessments are two crucial yet repetitive ta... more Fetal biometry (FB) and amniotic fluid volume (AFV) assessments are two crucial yet repetitive tasks of fetal ultrasound screening scans that help detect potential life-threatening conditions, however, they suffer from reproducibility and reliability issues. Advances in deep learning have led to new applications in measurement automation in fetal ultrasound, showcasing human-level performances in several fetal ultrasound tasks. However, most of the studies performed are retrospective “in silico” studies and few include African patients in their dataset. Here we develop and prospectively assess the performance of deep learning models for an end-to-end FB and AFV automation from a newly constructed database of 172 293 de-identified Moroccan fetal ultrasound images in addition to publicly available datasets. They were tested on prospectively acquired video clips from 172 patients forming a consecutive series gathered at four healthcare centers in Morocco. Our results show the 95% limit...

Springer eBooks, Sep 1, 2022

Technology has transformed traditional educational systems around the globe; integrating digital ... more Technology has transformed traditional educational systems around the globe; integrating digital learning tools into classrooms offers students better opportunities to learn efficiently and allows the teacher to transfer knowledge more easily. In recent years, there have been many improvements in smart classrooms. For instance, the integration of facial emotion recognition systems (FER) has transformed the classroom into an emotionally aware area using the power of machine intelligence and IoT. This paper provides a consolidated survey of the state-of-the-art in the concept of smart classrooms and presents how the application of FER systems significantly takes this concept to the next level.

About ten years ago, the double behest of late Driss Aboutajdine and El Mustapha Mouaddib permitt... more About ten years ago, the double behest of late Driss Aboutajdine and El Mustapha Mouaddib permitted setting up research partnership on the use of image processing and cultural heritage. In 2015, despite his workload, Professor Driss Aboutajdine has put all his energy so a common complementary action could take place and occur, convening hence the numerical sciences, precisely 3D techniques, serving cultural heritage. This action went on to give birth to Athar-3D project, with the ambition to resolve questions pertaining to 3D modeling and computer vision having along a positive impact on cultural and architectural heritage perception. The research we carried out in this framework aims to the digitizing of Hassan Mosque, its reconstitution and the achievement of mechanism and application to heighten awareness and to better know and communicate about cultural heritage matter. To our knowledge, this is the first work of its kind and with this scientific extent on cultural and architect...

The overflow of new technologies that enable live streams of big data has availed healthcare moni... more The overflow of new technologies that enable live streams of big data has availed healthcare monitoring in real time. A massive amount of medical data generated by IoT wearable devices can be transmitted today in realtime to medical professionals. However, the high velocity and time sensitivity of such data make it difficult to include the analysis and processing to extract insights in real-time. This work presents an approach for patient health monitoring based on visual analytics to help collecting, processing, and visualizing medical data streams in real-time. A first prototype of this system was developed, and initial results are presented.

Advanced Technologies for Humanity, 2022

2016 5th International Conference on Multimedia Computing and Systems (ICMCS), 2016

The Normalized Difference Vegetation Index was introduced for monitoring vegetation dynamics. Thi... more The Normalized Difference Vegetation Index was introduced for monitoring vegetation dynamics. This index can be extracted from multispectral sensor data, such as Landsat and MODIS sensors, and therefore the NDVI can be obtained with high spatial resolution but low temporal resolution when using Landsat or with high temporal resolution but low spatial resolution when using MODIS. Spatiotemporal fusion methods were proposed as a solution for this limitation. By using these methods, images with high spatial and high temporal resolution can be obtained. STARFM, ESTARFM and FSDAF are ones of the methods that have been successfully applied for spatiotemporal fusion. The objective of this study is to compare and evaluate these three methods and apply it on actual NDVI Landsat 8 and MODIS data in the region of Tadla in Morocco, to generate daily NDVI at 30m resolution. This evaluation was supervised by experts in CRTS and this through two approaches. The evaluation approach one is applying ...

2018 9th International Symposium on Signal, Image, Video and Communications (ISIVC), 2018

3D digitalization becomes a real need in many domains. It allows capturing and reproducing real-w... more 3D digitalization becomes a real need in many domains. It allows capturing and reproducing real-world objects or environments in order to understand and preserve them. It can be achieved by using either photogrammetry or laser scanner. Hence, a 3D point cloud is generated by merging several scans from several scanner positions. Nonetheless, the difficult challenge of this digitalization is to guarantee the quality of the cloud. This quality is mainly measured by completeness, resolution and accuracy. In this paper, we propose a criterion to estimate the completeness and a solution improving the accuracy of the point cloud and withdrawing needless points. Indeed, boolean operations on polygons for calculating the completeness of a predetermined convex area from data of the previous scanner positions is proposed. This approach does not need any sampling of the supposed environment. Furthermore, nearest neighborhood of each point of the cloud and neighbors coming from multiple scans are compared in order to remove useless points and improve the accuracy of digitalization. For evaluation purposes, we consider model of the Hassan mosque in Rabat (Morocco). Thus, the quality of this model was quantified by the three above considered measures.

International journal of imaging and robotics, 2018

The objects tracking applications are ubiquitous and largely discussed to address the problem of ... more The objects tracking applications are ubiquitous and largely discussed to address the problem of model object tracking in images sequence. Then we propose an adapted model object over the omnidirectional image provided by the catadioptric system, using the multiscale processing (MS). This processing based on Generalized Gaussian Density (GGD) model and Kullback-Leibler Distance (KLD) take into account the deformed geometry in those images. The aim of this work is to divide an image into a number of blocks, to model these blocks by GGD parameters and computing the similarity using the KLD between the current image block that contains the object and the candidate blocks. The tracking performance of the proposed system is further improved using Spatial Overlapping Estimation (SOE), the ROC curve. Experimental results show that the proposed approach is efficient for object tracking paradigm by comparison with the classical BMM and CAM-Shift Algorithms.

Journal of Computer Science, 2020

Image descriptor have been widely applied in many computer visions and image understanding applic... more Image descriptor have been widely applied in many computer visions and image understanding applications including pattern recognition, robotic, video surveillance, camera calibration and image retrieval, etc. Invariants features are robust when apply several transformations of photometry (illumination, blur, noise, JPEG compression) and transformations of geometry (scaling, rotation, translation and viewpoint change). In this study, we present representation and matching region descriptors. Consequently, a set of region used provided by catadioptric system for evaluation of the performance. These regions are normalized by unit circle form with form and size change. In this contribution, the image descriptors of regions used is Moment's Zernike. They are most suitable invariants in omnidirectional context thanks to the polar coordinates used both omnidirectional geometry and Zernike Moments formulation. The aim is realize a robust matching between object's block by using a me...

2019 International Conference on Intelligent Systems and Advanced Computing Sciences (ISACS), 2019

The objects tracking applications are ubiquitous and largely discussed in computer vision field. ... more The objects tracking applications are ubiquitous and largely discussed in computer vision field. Nevertheless, the toughest challenge encountered in the catadioptric system is images geometry deformations. Nevertheless, these images have significant distortions that that bring us to take them into account during processing. In this paper, we propose an adapted tracking according to spherical coordinates over the 2D image. We present a novel content based omnidirectional image provided by the catadioptric system for object tracking model using a Spherical object tracking (SOT). Our statistical approach uses a new search algorithm called Ring Search (RSA), the Generalized Gaussian Distribution (GGD) as well as the Kullback-Leibler Distance (KLD). In SOT, we split images into several macro-blocks according to spherical coordinates, each macro-block are modelled by the GGD parameters. After that, we compute the similarity between the current bloc and the candidate one onto the search zo...

L'etude porte sur un Systeme Stereo Catadioptrique multiPlan (SSCP) constitue d'une uniqu... more L'etude porte sur un Systeme Stereo Catadioptrique multiPlan (SSCP) constitue d'une unique camera perspective et deux miroirs plans judicieusement positionnes. En positionnant un objet entre les miroirs plans et la camera, cinq vues en sont observees simultanement. Dans cet article, nous abordons la modelisation et l'etalonnage geometrique de SSCP. Les points d'interet detectes dans la vue directe servent de reference pour la recherche de correspondances sous la contrainte d'une homographie minimisant l'erreur photometrique entre voisinages. La correspondance mene a la reconstruction 3D des points dont les resultats demontrent la qualite de la methode de recherche de correspondances et que la reconstruction 3D avec une image d'un SSCP est possible.

2018 25th IEEE International Conference on Image Processing (ICIP), 2018

In this paper, we propose a descriptor for image matching under multiple mirror reflections. Inde... more In this paper, we propose a descriptor for image matching under multiple mirror reflections. Indeed, existing adaptations of SIFT for the mirror transformation are not successful when object and mirrors orientations are not constrained. Hence, we propose to combine MIFT and Affine-SIFT descriptors as the Affine Mirror Invariant Feature Transform (AMIFT). The experimental results and given evaluation show that our proposed descriptor outperforms MIFT and ASIFT on both synthetic and real images datasets.

Journal of Computer Science, 2020

Tracking objects on video sequences is a very challenging task in computer vision applications. H... more Tracking objects on video sequences is a very challenging task in computer vision applications. However, there is few articles that deal with this topic in catadioptric vision. This paper describes a new approach of omnidirectional images (gray level) processing based on inverse stereographic projection in the image plane. Our work is based on minimizing the distance between two models. The model named von Mises-Fisher distribution have as input the gabor phase and the measure used is Kullback-Leibler Divergence (KLD). In one hand, this model matching respect the deformed geometry of omnidirectional images due to using the spherical neighbourhood. In the other hand, the simulation results show that our approach gives as better performance in terms of overlapping estimation.

Image and Vision Computing, 2020

This paper presents a Riemannian approach for free-space extraction and path planning using color... more This paper presents a Riemannian approach for free-space extraction and path planning using color catadioptric vision. The problem is formulated considering color catadioptric images as Riemannian manifolds and solved using the Riemannian Eikonal equation with an anisotropic fast marching numerical scheme. This formulation allows the integration of adapted color and spatial metrics in an incremental process. First, the traversable ground (namely free-space) is delimited using a color structure tensor built on the multidimensional components of the catadioptric image. Then, the Eikonal equation is solved in the image plane incorporating a generic metric tensor for central catadioptric systems. This built Riemannian metric copes with the geometric distortions in the catadioptric image plane introduced by the curved mirror in order to compute the geodesic distance map and the shortest path between image points. We present comparative results using Euclidean and Riemannian distance transforms and show the effectiveness of the Riemannian approach to produce safest path planning.

Computer Vision and Image Understanding, 2018

Images produced by omnidirectional catadioptric systems provide a larger field of view than conve... more Images produced by omnidirectional catadioptric systems provide a larger field of view than conventional cameras. However, these images contain significant radial distortions making classical processing unadapted. In addition, color information is almost neglected in omnidirectional imaging. In this paper, we propose a unifying framework, for central catadioptric color image processing, using Riemannian embedding that deals simultaneously with the geometric deformation due to the use of curved mirrors, and the multi-dimensional characteristic of the image. Based on the introduced Riemannian metric, we derive an adapted Gaussian kernel which is essential in widely used image processing. The resulting new formulation is then applied to various image processing: Image smoothing, Difference of Gaussians filtering and scalespace analysis, edge extraction and corner feature detection using Gaussian derivatives. The experiments illustrate the potential of the proposed approach, and show the higher quality of the adapted processing.

Proceedings of the Fifth International Conference on Telecommunications and Remote Sensing, 2016

Satellite image sensors are able to give images at high temporal resolution as the MODIS sensor t... more Satellite image sensors are able to give images at high temporal resolution as the MODIS sensor that gives an image every day but with low spatial resolution, or at high spatial resolution as the Landsat sensor that gives images at 30m but with a revisit cycle of 16 days. Thus, this sensors are not able to give images with both high spatial and high temporal resolution. This need has become more and more absolute for many applications. Therefore spatiotemporal fusion methods were proposed. By applying these methods on images from different sensors with different spatial and temporal resolution, we can take the advantage of the high spatial and high temporal resolution of these sensors. As a result we get an image with both high spatial and high temporal resolution. We introduce in this paper a new method, the Wavelet base Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (WESTARFM), which is an improvement of the ESTARFM method. It uses the principle of wavelet transform with the original ESTARFM method. We have applied our method to predict daily NDVI in a study site in an irrigated zone in the region of TADLA in MOROCCO. Results have been compared with other methods.

Research Journal of Applied Sciences, Engineering and Technology, 2014

The problem of image denoising is largely discussed in the literature. It is a fundamental prepro... more The problem of image denoising is largely discussed in the literature. It is a fundamental preprocessing task, and an important step in almost all view compared to conventional perspectives images, however, the treatments are thus not appropriate for those deformed omnidirectional adaptation of an adaptation to Stein block thresholding method to omnidirectional images. We will adapt different treatments in order to take into account the nature of omnidirectional images

Proceedings of the 9th International Conference on Computer Vision Theory and Applications, 2014

The current work addresses the problem of 3D model tracking in the context of omnidirectional vis... more The current work addresses the problem of 3D model tracking in the context of omnidirectional vision in order to object tracking. However, there is few articles dealing this problem in catadioptric vision. This paper is an attempt to describe a new approach of omnidirectional images (gray level) processing based on inverse stereographic projection in the half-sphere. We used the spherical model. For object tracking, The object tracking method used is snake, with optimization using the Greedy algorithm, by adapting its different operators. This method algorithm will respect the deformed geometry of omnidirectional images such as the spherical neighbourhood, the spherical gradient and reformulation of optimization algorithm on the spherical domain. This tracking method-that we call spherical snake-permit to know the change of the shape and the size of 2D object in different replacements in the spherical image.

Computer Science Research Notes

The recent proliferation of advanced data collection technologies for Patient Generated Health Da... more The recent proliferation of advanced data collection technologies for Patient Generated Health Data (PGHD) has made remote health monitoring more accessible. However, the complex nature of the big volume of medical generated data presents a significant challenge for traditional patient monitoring approaches, impeding the effective extraction of useful information. In this context, it is imperative to develop a robust and cost-effective framework that provides the scalability and deals with the heterogeneity of PGHD in real-time. Such a system could serve as a reference and would guide future research for monitoring patient undergoing a treatment at home conditions. This study presents a real-time visual analytics framework offering insightful visual representations of the multimodal big data. The proposed system was designed following the principles of User Centered Design (UCD) to ensure that it meets the needs and expectations of medical practitioners. The usability of this framew...

Lecture notes in networks and systems, 2023

Fetal biometry (FB) and amniotic fluid volume (AFV) assessments are two crucial yet repetitive ta... more Fetal biometry (FB) and amniotic fluid volume (AFV) assessments are two crucial yet repetitive tasks of fetal ultrasound screening scans that help detect potential life-threatening conditions, however, they suffer from reproducibility and reliability issues. Advances in deep learning have led to new applications in measurement automation in fetal ultrasound, showcasing human-level performances in several fetal ultrasound tasks. However, most of the studies performed are retrospective “in silico” studies and few include African patients in their dataset. Here we develop and prospectively assess the performance of deep learning models for an end-to-end FB and AFV automation from a newly constructed database of 172 293 de-identified Moroccan fetal ultrasound images in addition to publicly available datasets. They were tested on prospectively acquired video clips from 172 patients forming a consecutive series gathered at four healthcare centers in Morocco. Our results show the 95% limit...

Springer eBooks, Sep 1, 2022

Technology has transformed traditional educational systems around the globe; integrating digital ... more Technology has transformed traditional educational systems around the globe; integrating digital learning tools into classrooms offers students better opportunities to learn efficiently and allows the teacher to transfer knowledge more easily. In recent years, there have been many improvements in smart classrooms. For instance, the integration of facial emotion recognition systems (FER) has transformed the classroom into an emotionally aware area using the power of machine intelligence and IoT. This paper provides a consolidated survey of the state-of-the-art in the concept of smart classrooms and presents how the application of FER systems significantly takes this concept to the next level.

About ten years ago, the double behest of late Driss Aboutajdine and El Mustapha Mouaddib permitt... more About ten years ago, the double behest of late Driss Aboutajdine and El Mustapha Mouaddib permitted setting up research partnership on the use of image processing and cultural heritage. In 2015, despite his workload, Professor Driss Aboutajdine has put all his energy so a common complementary action could take place and occur, convening hence the numerical sciences, precisely 3D techniques, serving cultural heritage. This action went on to give birth to Athar-3D project, with the ambition to resolve questions pertaining to 3D modeling and computer vision having along a positive impact on cultural and architectural heritage perception. The research we carried out in this framework aims to the digitizing of Hassan Mosque, its reconstitution and the achievement of mechanism and application to heighten awareness and to better know and communicate about cultural heritage matter. To our knowledge, this is the first work of its kind and with this scientific extent on cultural and architect...

The overflow of new technologies that enable live streams of big data has availed healthcare moni... more The overflow of new technologies that enable live streams of big data has availed healthcare monitoring in real time. A massive amount of medical data generated by IoT wearable devices can be transmitted today in realtime to medical professionals. However, the high velocity and time sensitivity of such data make it difficult to include the analysis and processing to extract insights in real-time. This work presents an approach for patient health monitoring based on visual analytics to help collecting, processing, and visualizing medical data streams in real-time. A first prototype of this system was developed, and initial results are presented.

Advanced Technologies for Humanity, 2022

2016 5th International Conference on Multimedia Computing and Systems (ICMCS), 2016

The Normalized Difference Vegetation Index was introduced for monitoring vegetation dynamics. Thi... more The Normalized Difference Vegetation Index was introduced for monitoring vegetation dynamics. This index can be extracted from multispectral sensor data, such as Landsat and MODIS sensors, and therefore the NDVI can be obtained with high spatial resolution but low temporal resolution when using Landsat or with high temporal resolution but low spatial resolution when using MODIS. Spatiotemporal fusion methods were proposed as a solution for this limitation. By using these methods, images with high spatial and high temporal resolution can be obtained. STARFM, ESTARFM and FSDAF are ones of the methods that have been successfully applied for spatiotemporal fusion. The objective of this study is to compare and evaluate these three methods and apply it on actual NDVI Landsat 8 and MODIS data in the region of Tadla in Morocco, to generate daily NDVI at 30m resolution. This evaluation was supervised by experts in CRTS and this through two approaches. The evaluation approach one is applying ...

2018 9th International Symposium on Signal, Image, Video and Communications (ISIVC), 2018

3D digitalization becomes a real need in many domains. It allows capturing and reproducing real-w... more 3D digitalization becomes a real need in many domains. It allows capturing and reproducing real-world objects or environments in order to understand and preserve them. It can be achieved by using either photogrammetry or laser scanner. Hence, a 3D point cloud is generated by merging several scans from several scanner positions. Nonetheless, the difficult challenge of this digitalization is to guarantee the quality of the cloud. This quality is mainly measured by completeness, resolution and accuracy. In this paper, we propose a criterion to estimate the completeness and a solution improving the accuracy of the point cloud and withdrawing needless points. Indeed, boolean operations on polygons for calculating the completeness of a predetermined convex area from data of the previous scanner positions is proposed. This approach does not need any sampling of the supposed environment. Furthermore, nearest neighborhood of each point of the cloud and neighbors coming from multiple scans are compared in order to remove useless points and improve the accuracy of digitalization. For evaluation purposes, we consider model of the Hassan mosque in Rabat (Morocco). Thus, the quality of this model was quantified by the three above considered measures.

International journal of imaging and robotics, 2018

The objects tracking applications are ubiquitous and largely discussed to address the problem of ... more The objects tracking applications are ubiquitous and largely discussed to address the problem of model object tracking in images sequence. Then we propose an adapted model object over the omnidirectional image provided by the catadioptric system, using the multiscale processing (MS). This processing based on Generalized Gaussian Density (GGD) model and Kullback-Leibler Distance (KLD) take into account the deformed geometry in those images. The aim of this work is to divide an image into a number of blocks, to model these blocks by GGD parameters and computing the similarity using the KLD between the current image block that contains the object and the candidate blocks. The tracking performance of the proposed system is further improved using Spatial Overlapping Estimation (SOE), the ROC curve. Experimental results show that the proposed approach is efficient for object tracking paradigm by comparison with the classical BMM and CAM-Shift Algorithms.

Journal of Computer Science, 2020

Image descriptor have been widely applied in many computer visions and image understanding applic... more Image descriptor have been widely applied in many computer visions and image understanding applications including pattern recognition, robotic, video surveillance, camera calibration and image retrieval, etc. Invariants features are robust when apply several transformations of photometry (illumination, blur, noise, JPEG compression) and transformations of geometry (scaling, rotation, translation and viewpoint change). In this study, we present representation and matching region descriptors. Consequently, a set of region used provided by catadioptric system for evaluation of the performance. These regions are normalized by unit circle form with form and size change. In this contribution, the image descriptors of regions used is Moment's Zernike. They are most suitable invariants in omnidirectional context thanks to the polar coordinates used both omnidirectional geometry and Zernike Moments formulation. The aim is realize a robust matching between object's block by using a me...

2019 International Conference on Intelligent Systems and Advanced Computing Sciences (ISACS), 2019

The objects tracking applications are ubiquitous and largely discussed in computer vision field. ... more The objects tracking applications are ubiquitous and largely discussed in computer vision field. Nevertheless, the toughest challenge encountered in the catadioptric system is images geometry deformations. Nevertheless, these images have significant distortions that that bring us to take them into account during processing. In this paper, we propose an adapted tracking according to spherical coordinates over the 2D image. We present a novel content based omnidirectional image provided by the catadioptric system for object tracking model using a Spherical object tracking (SOT). Our statistical approach uses a new search algorithm called Ring Search (RSA), the Generalized Gaussian Distribution (GGD) as well as the Kullback-Leibler Distance (KLD). In SOT, we split images into several macro-blocks according to spherical coordinates, each macro-block are modelled by the GGD parameters. After that, we compute the similarity between the current bloc and the candidate one onto the search zo...

L'etude porte sur un Systeme Stereo Catadioptrique multiPlan (SSCP) constitue d'une uniqu... more L'etude porte sur un Systeme Stereo Catadioptrique multiPlan (SSCP) constitue d'une unique camera perspective et deux miroirs plans judicieusement positionnes. En positionnant un objet entre les miroirs plans et la camera, cinq vues en sont observees simultanement. Dans cet article, nous abordons la modelisation et l'etalonnage geometrique de SSCP. Les points d'interet detectes dans la vue directe servent de reference pour la recherche de correspondances sous la contrainte d'une homographie minimisant l'erreur photometrique entre voisinages. La correspondance mene a la reconstruction 3D des points dont les resultats demontrent la qualite de la methode de recherche de correspondances et que la reconstruction 3D avec une image d'un SSCP est possible.

2018 25th IEEE International Conference on Image Processing (ICIP), 2018

In this paper, we propose a descriptor for image matching under multiple mirror reflections. Inde... more In this paper, we propose a descriptor for image matching under multiple mirror reflections. Indeed, existing adaptations of SIFT for the mirror transformation are not successful when object and mirrors orientations are not constrained. Hence, we propose to combine MIFT and Affine-SIFT descriptors as the Affine Mirror Invariant Feature Transform (AMIFT). The experimental results and given evaluation show that our proposed descriptor outperforms MIFT and ASIFT on both synthetic and real images datasets.

Journal of Computer Science, 2020

Tracking objects on video sequences is a very challenging task in computer vision applications. H... more Tracking objects on video sequences is a very challenging task in computer vision applications. However, there is few articles that deal with this topic in catadioptric vision. This paper describes a new approach of omnidirectional images (gray level) processing based on inverse stereographic projection in the image plane. Our work is based on minimizing the distance between two models. The model named von Mises-Fisher distribution have as input the gabor phase and the measure used is Kullback-Leibler Divergence (KLD). In one hand, this model matching respect the deformed geometry of omnidirectional images due to using the spherical neighbourhood. In the other hand, the simulation results show that our approach gives as better performance in terms of overlapping estimation.

Image and Vision Computing, 2020

This paper presents a Riemannian approach for free-space extraction and path planning using color... more This paper presents a Riemannian approach for free-space extraction and path planning using color catadioptric vision. The problem is formulated considering color catadioptric images as Riemannian manifolds and solved using the Riemannian Eikonal equation with an anisotropic fast marching numerical scheme. This formulation allows the integration of adapted color and spatial metrics in an incremental process. First, the traversable ground (namely free-space) is delimited using a color structure tensor built on the multidimensional components of the catadioptric image. Then, the Eikonal equation is solved in the image plane incorporating a generic metric tensor for central catadioptric systems. This built Riemannian metric copes with the geometric distortions in the catadioptric image plane introduced by the curved mirror in order to compute the geodesic distance map and the shortest path between image points. We present comparative results using Euclidean and Riemannian distance transforms and show the effectiveness of the Riemannian approach to produce safest path planning.

Computer Vision and Image Understanding, 2018

Images produced by omnidirectional catadioptric systems provide a larger field of view than conve... more Images produced by omnidirectional catadioptric systems provide a larger field of view than conventional cameras. However, these images contain significant radial distortions making classical processing unadapted. In addition, color information is almost neglected in omnidirectional imaging. In this paper, we propose a unifying framework, for central catadioptric color image processing, using Riemannian embedding that deals simultaneously with the geometric deformation due to the use of curved mirrors, and the multi-dimensional characteristic of the image. Based on the introduced Riemannian metric, we derive an adapted Gaussian kernel which is essential in widely used image processing. The resulting new formulation is then applied to various image processing: Image smoothing, Difference of Gaussians filtering and scalespace analysis, edge extraction and corner feature detection using Gaussian derivatives. The experiments illustrate the potential of the proposed approach, and show the higher quality of the adapted processing.

Proceedings of the Fifth International Conference on Telecommunications and Remote Sensing, 2016

Satellite image sensors are able to give images at high temporal resolution as the MODIS sensor t... more Satellite image sensors are able to give images at high temporal resolution as the MODIS sensor that gives an image every day but with low spatial resolution, or at high spatial resolution as the Landsat sensor that gives images at 30m but with a revisit cycle of 16 days. Thus, this sensors are not able to give images with both high spatial and high temporal resolution. This need has become more and more absolute for many applications. Therefore spatiotemporal fusion methods were proposed. By applying these methods on images from different sensors with different spatial and temporal resolution, we can take the advantage of the high spatial and high temporal resolution of these sensors. As a result we get an image with both high spatial and high temporal resolution. We introduce in this paper a new method, the Wavelet base Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (WESTARFM), which is an improvement of the ESTARFM method. It uses the principle of wavelet transform with the original ESTARFM method. We have applied our method to predict daily NDVI in a study site in an irrigated zone in the region of TADLA in MOROCCO. Results have been compared with other methods.

Research Journal of Applied Sciences, Engineering and Technology, 2014

The problem of image denoising is largely discussed in the literature. It is a fundamental prepro... more The problem of image denoising is largely discussed in the literature. It is a fundamental preprocessing task, and an important step in almost all view compared to conventional perspectives images, however, the treatments are thus not appropriate for those deformed omnidirectional adaptation of an adaptation to Stein block thresholding method to omnidirectional images. We will adapt different treatments in order to take into account the nature of omnidirectional images