Johel Miteran

University of Burgundy | UB · Imvia

For several decades, the camera spatial resolution is gradually increasing with the CMOS technology evolution. The image sensors provide more and more pixels, generating new constraints for suitable optics. As an alternative, promising solutions propose super-resolution (SR) techniques to reconstruct high-resolution images or video without modifyin...

Objective The aim of our study was to evaluate the impact of aortic root replacement by graft on the elastic properties of the descending thoracic aorta using cardiac magnetic resonance imaging (MRI) and automatic post-processing. Materials and methods Nineteen patients were operated for an aortic root aneurysm. Cardiac MRI was performed before an...

In this work, we investigate biometrics applied on 2D faces in order to secure areas requiring high security level. Based on emerging deep learning methods (more precisely transfer learning) as well as two classical machine learning techniques (Support Vector Machines and Random Forest), different approaches have been used to perform person authent...

Since several decades, the camera spatial resolution is gradually increasing with the CMOS technology evolution. The image sensors provide more and more pixels, generating new constraints for the suitable optics. As an alternative, promising solutions propose Super Resolution (SR) image reconstruction to extend the image size without modifying the...

The aim of this paper is to highlight differences between classical machine learning and transfer learning applied to low cost real-time face authentication. Furthermore, in an access control context, the size of biometric data should be minimized so it can be stored on a remote personal media. These constraints have led us to compare only lightest...

Despite the evolution of technologies, high-quality image acquisition systems design is a complex challenge. Indeed, during the image acquisition process, the recorded image does not fully represent the real visual scene. The recorded information could be partial due to dynamic range limitation and degraded due to distorsions of the acquisition sys...

Parameters of aortic elasticity, such as aortic compliance or aortic distensibility, can be estimated from cine-MRI through the knowledge of the aortic contour on each image. In this context, a completely automatic method for the measurement of aortic elasticity is proposed in this study, and compared with previously published methods which are not...

Depuis 2016, afin de minimiser les risques pour la vie privée, la Commission Nationale de l’Informatique et des Libertés (la CNIL) privilégie les dispositifs de sécurité biométrique garantissant à l’usager la maîtrise de ses données personnelles. Ce papier présente une étude d’adéquation algorithme et architecture appliquée au problème de stockage...

Prostate cancer is considered to be the third and sixth leading cause of death from cancer in men in developed and developing countries, respectively. As Multiparametric Magnetic Resonance Imaging (mp-MRI) and Magnetic Resonance Spectroscopic Imaging (MRSI) play an important role in the detection and the localization of cancerous tissues, in this p...

Multiparametric-magnetic resonance imaging (mp-MRI) has demonstrated, in many studies, its potential in prostate cancer detection and analysis. We propose a supervised classification approach based on mp-MRI data base of 20 patients, in order to localize prostate cancer and to achieve a cartographic representation of the prostate voxels based on cl...

Smart camera, i.e. cameras that are able to acquire and process images in real-time, is a typical example of the new embedded computer vision systems. A key example of application is automatic fall detection, which can be useful for helping elderly people in daily life. In this paper, we propose a methodology for development and fast-prototyping of...

JPEG2000 is an international standard for still images intended to overcome the shortcomings of the existing JPEG standard. Compared to JPEG image compression techniques, JPEG2000 standard has not only better not only has better compression ratios, but it also offers some exciting features. As it's hard to meet the real-time requirement of image co...

We propose a SVM-based approach to detect falls in several home environments using an optimised descriptor adapted to real-time tasks.We build an optimised spatiooral descriptor named STHFa-SBFSusing several combinations of transformations of geometrical features, thanks to feature selection. We study the combinations of usual transformations of th...

JPEG 2000 is an international standard for still images intended to overcome the shortcomings of the existing JPEG standard. Compared to JPEG image compression techniques, JPEG 2000 standard has not only better not only has better compression ratios, but it also offers some exciting features. As it’s hard to meet the real-time requirement of image...

Raw output data from image sensors tends to exhibit a form of bias due to slight on-die variations between photodetectors, as well as between amplifiers. The resulting bias, called fixed pattern noise (FPN), is often corrected by subtracting its value, estimated through calibration, from the sensor’s raw signal. This paper introduces an on-line sce...

Smart cameras are used in a large range of applications. Usually the smart cameras transmit the video or/and extracted information from the video scene, frequently on compressed format to fit with the application requirements. An efficient hardware accelerator that can be adapted and provide the required coding performances according to the events...

Abstract. We propose a supervised approach to detect falls in a home environment using an optimized descriptor adapted to real-time tasks. We introduce a realistic dataset of 222 videos, a new metric allowing evaluation of fall detection performance in a video stream, and an automatically optimized set of spatio-temporal descriptors which fed a sup...

We propose a supervised approach to detect falls in a home environment using an optimized descriptor adapted to real-time tasks. We introduce a realistic dataset of 222 videos, a new metric allowing evaluation of fall detection performance in a video stream, and an automatically optimized set of spatio-temporal descriptors which fed a supervised cl...

We propose a supervised approach to detect falls in a home environment using an optimized descriptor adapted to real-time tasks. We introduce a realistic dataset of 222 videos, a new metric allowing evaluation of fall detection performance in a video stream, and an automatically optimized set of spatio-temporal descriptors which fed a supervised cl...

We propose an automatic approach to detect falls in home environment. A Support Vector Machine based classifier is fed by a set of selected features extracted from human body sil-houette tracking. The classifier is followed by filtering operations taking into account the temporal nature of a video. The features are based on height and width of huma...

Despite the diversity of video compression standard, the motion estimation still remains a key process which is used in most of them. Moreover, the required coding performances (bit-rate, PSNR, image spatial resolution, etc.) depend obviously of the application, the environment and the network communication. The motion estimation can therefore be a...

Despite the diversity of video compression standard, the motion estimation still remains a key process which is used in most of them. Moreover, the required coding performances (bit-rate, PSNR, image spatial resolution, etc.) depend obviously of the application, the environment and the network communication. The motion estimation can therefore be a...

Prostate cancer is the most common cancer in men over 50 years of age and it has been shown that nuclear magnetic resonance spectra are sensitive enough to distinguish normal and cancer tissues. In this paper, we propose a classification technique of spectra from magnetic resonance spectroscopy. We studied automatic classification with and without...

In the context of leaf roughness study for precision spray- ing applications, this article deals with its characterisation by computer vision techniques. Texture analysis is a pri- mordial step for applications based on image analysis such as medical or agronomical imaging. The aim is to classify textures after extraction of discriminating features...

Despite the diversity of video compression standard, the motion estimation still remains a key process which is used in most of them. Moreover, the required coding performances (bit-rate, PSNR, image spatial resolution,etc.) depend obviously of the application, the environment and the network communication. The motion estimation can therefore be ad...

Motion estimation represents a key module in video compression. The Reconfigurable Video Coding context (RVC) requires proposing a flexible solution for motion estimation. The motion estimation performance should be modified to fit with the user or the environment's constraints. Depending on the required performances fixed by the application, a ful...

The large numbers of sub-windows addresses require the use of intermediate memories, which will manage the communication between the different blocks. At any given time, Block 1 processes on image In and stores the addresses of its positively labeled sub-windows in a memory (mem.1). At the same time Block 2 processes an image In-1 but only the sub-...

In the context of plant leaf roughness analysis for precision spraying, this study explores the capability and the performance of some combinations of pattern recognition and computer vision techniques to extract the roughness feature. The techniques merge feature extraction, linear and nonlinear dimensionality reduction techniques, and several kin...

Motion estimation represents a key module in video compression. The RVC context requires proposing a flexible solution for motion estimation. According to the nature of the application, a full search is sometimes not suitable, hence, alternative fast/reduced solutions should be considered. This paper proposes a model and implementation of a flexibl...

Object detection forms the first step of a larger setup for a wide variety of computer vision applications. The focus of this paper is the implementation of a real-time embedded object detection system while relying on high-level description language such as SystemC. Boosting-based object detection algorithms are considered as the fastest accurate...

Dans un contexte de classification de texture par caractérisation d'invariant, cet article propose de comparer les performances de différentes combinaisons croisées de 13 techniques de réduction de dimensionnalité et 6 méthodes de classification. Les performances sont évaluées et comparées sous la forme d'erreur de classification. Dans le but de te...

Motion estimation represents a key module in video compression. The RVC context requires proposing a flexible solution for motion estimation. According to the nature of the application, a full search is sometimes not suitable, hence, alternative fast/reduced solutions should be considered. This paper proposes a model and implementation of a flexibl...

In the context of texture classification, this article explores the capacity and the performance of some combinations of feature extraction, linear and nonlinear dimensionality reduction techniques and several kinds of classification methods. The performances are evaluated and compared in term of classification error. In order to test our texture c...

The face detection is a fundamental prerequisite step in the process of face recognition. The focus of this paper is the implementation of a real time embedded face detection system while relying on high level description language such as SystemC. Recently, the boosting based object detection algorithms proposed by have gained a lot of attention an...

This paper is about generalized Fourier descriptors, and their application to the research of invariants under group actions. A general methodology is developed, crucially related to Pontryagin’s, Tannaka’s, Chu’s and Tatsuuma’s dualities, from abstract harmonic analysis. Application to motion groups provides a general methodology for pattern recog...

In this paper, we describe a general method using the abstract non-Abelian Fourier transform to construct “rich” invariants of group actions on functional spaces. In fact, this method is inspired of a classical method from image analysis: the method of Fourier descriptors, for discrimination among “contours” of objects. This is the case of the Abel...

One of the most important activity of agricultural research insititutes concerns the agronomical experiments done under different conditions needing many land observations and valuations to quantify several variables. These observations, although generally accurate, are visually done by the agriculturist technicians and present numerous drawbacks:...

Fourier Descriptors can be used as feature vector components in various applications, such as real-time color object recognition or image retrieval. The full process is composed of the feature extraction followed by a classification step performed using Support Vector Machine (SVM). In order to accelerate the computation of Fourier Descriptors, a h...

This paper describes a new approach for detection of curvilinear regions. These features detection can be useful for any matching based algorithm such as stereoscopic vision. Our detector is based on curvilinear structure model, defined observing the real world. Then, we propose a multi- scale search algorithm of curvilinear regions and we report s...

The rapid development of information systems has lead in many ways to the definition of advanced authorization and access control models. Recent models have considered context (such as time, location, age, etc.) as key issue to allow flexible and dynamic policy specification. However, these models are application-dependent, text-based, complex to m...

An architecture for fast video object recognition is proposed. This architecture is based on an approximation of featureextraction function: Zernike moments and an approximation of a classification framework: Support Vector Machines (SVM). We review the principles of the moment-based method and the principles of the approximation method: dithering....

Acquiring 3D data of human face is a general problem which can be applied in face recognition, virtual reality, and many other applications. It can be solved using stereovision. This technique consists in acquiring data in three dimensions from two cameras. The aim is to implement an algorithmic chain which makes it possible to obtain a three-dimen...

Fourier descriptors have been used successfully in the past to grey-level images, rigid bodied object. Here we used motion descriptors (MD) introduced recently by Gauthier et al., combined with Zernike Moments (ZM), in order to perform a recognition task in colour images. The feature vector for the MD obtained for each object appears to be unique a...

This paper describes a study for a real time embedded face detection system. Recently, the boosting based face detection algorithms proposed by [(Viola, P and Jone, M, 2001); (Lienhart, R, et al., 2003)] have gained a lot of attention and are considered as the fastest accurate face detection algorithms today. However, the embedded implementation of...

Face detection and recognition has many applications in a variety of fields such as security system, videoconferencing and identification. Face classification is currently implemented in software. A hardware implementation allows real-time processing, but has higher cost and time to-market. The objective of this work was to implement a classifier b...

We present a classification work performed on industrial parts using artificial vision, a support vector machine (SVM), boosting, and a combination of classifiers. The object to be controlled is a coated heater used in television sets. Our project consists of detecting anomalies under manufacturer production, as well as in classifying the anomalies...

This paper presents a classification work performed on industrial parts using artificial vision, Support Vector Machine (SVM), Boosting and a combination of classifiers. The object to be controlled is a coated heater used in television set. Our project consists of detecting anomalies under manufacturer production as well as in classifying the anoma...

We propose a method and a tool for automatic generation of hardware implementation of a decision rule based on the Adaboost algorithm. We review the principles of the classification method and we evaluate its hardware implementation cost in terms of FPGA's slice, using different weak classifiers based on the general concept of hyperrectangle. The m...

We present a multiscale edge detection algorithm whose aim is to detect edges whatever their slope. Our work is based on a generalization of the Canny-Deriche filter, characterized by a more realistic edge than the traditional step shape edge. The filter impulse response is used to generate a multiscale edge detection scheme. For the merging of the...

This paper describes a motion estimation co-processor architecture that explicitly separates the implementation stages consisting of data access to the search window and the evaluation of the matching criterion from the implementation of the search strategy. The architecture is modular and can be re-configured according to the different MPEG video...

This paper presents a classification work performed on industrial parts using artificial vision, SVM and a combination of classifiers. Prior to this study, defect detection was performed by human inspectors. Unfortunately, the time involved in the inspection procedure was far too long and the misclassification rate too high. Our project consists in...

This paper is about the implementation of a part of the JPEG2000 algorithm (MQ-decoder and arithmetic decoder) in a FPGA by using dynamic reconfiguration. The implementation is done on an architecture named ARDOISE, created to study fine grain dynamic reconfiguration of FPGAs.

We propose a method of real-time implementation of an approximation of the support vector machine decision rule. The method uses an improvement of a supervised classification method based on hyperrectangles, which is useful for real-time image segmentation. We increase the classification and speed performances using a combination of classification...

A real-time implementation of an approximation of the support vector machine (SVM) decision rule is proposed. This method is based on an improvement of a supervised classification method using hyperrectangles, which is useful for real-time image segmentation. The final decision combines the accuracy of the SVM learning algorithm and the speed of a...

In this paper, we propose a method of implementation improvement of the decision rule of the support vector machine, applied to real-time image segmentation. We present very high speed decisions (approximately 10 ns per pixel) which can be useful for detection of anomalies on manufactured parts. We propose an original combination of classifiers all...

Nous présentons dans cet article une application complète des « Support Vector Machine » au contrôle qualité par vision artificielle de pièces à géométrie complexe. Nous précisons le cadre pratique dans lequel s'effectuent les opérations, la nature des défauts à détecter ainsi que les techniques d'extraction des paramètres discriminants. Puis nous...

FPGA components are widely used today to perform various algorithms (digital filtering) in real time. The emergence of Dynamically Reconfigurable (DR) FPGAs made it possible to reduce the number of necessary resources to carry out an image processing application (tasks chain). We present in this article an image processing application (image rotati...

The paper describes a real-time system for visual inspection of textured industrial parts -CRT cathodes. Four types of anomalies are detected: smooth surfaces, bumps, missing material and hollow knocked surfaces. In order to distinguish defective and acceptable zones with minimum error, both optimal lighting parameters and most discriminative featu...

We present a study of two classification methods used in order to control, in real-time, some industrial parts. We present the practical framework in which the operations are carried out, the nature of the anomaly to be detected as well as the feature extraction method. We tested the two classification techniques, with different algorithm complexit...

The problem to acquire 3D data of human face can be applied in face recognition, virtual reality, and many other applications. It can be solved using stereovision. This technique consistes in acquiring data in three dimensions from two cameras. The aim is to implement an algorithmic chain which makes it possible to obtain a three-dimensional space...

Quality control by artificial vision is getting more and more widespread within the industry. Indeed, in many cases, industrial applications require a control with high stability performance, satisfying high production rate. The purpose of this paper is to present a method to detect in real time defects located on the circumference of industrial pa...