Analyse et implantation de processeurs optiques de compression-décompression optique basées sur les normes JPEG et JPEG2000

L accroissement très rapide de l utilisation des images de très bonne qualité dans les domaines des multimédias, des jeux, des transmissions satellites et de l imagerie médicale, pose deux grands problèmes: la transmission et le stockage de données. Pour gagner aussi bien en temps qu en mémoire, il est nécessaire de compresser ces images tout en gardant une bonne qualité. Cependant, malgré l origine optique de l image, le traitement se fait souvent numériquement. Ce qui entraîne une perte de temps lié à la numérisation de cette image avant de pouvoir appliquer l algorithme de compression souhaitée. De plus, comprimer numériquement des informations de plus en plus complexes (images hautes résolutions par exemple) exige des temps de calcul très coûteux, malgré les progrès de l informatique. Cette thèse traite le problème de la compression des images fixes, mais d un point de vue de l implantation optique afin de réduire la taille de l information en éliminant les informations redondantes, cela dans le but de gagner en espace mémoire et permettre une transmission rapide. En effet, l optique cohérente offre la possibilité de réaliser la transformation d une image bidimensionnelle quasi-instantané (comme par exemple la transformation de Fourier). Cette propriété est utilisée depuis longtemps pour rechercher un objet particulier (cible) dans une scène quelconque (technique de corrélation optique). Fort de l expérience acquise dans notre laboratoire dans le domaine du traitement optique de l information, nous avons développé deux méthodes de compression avec implantation optique adaptées aux normes JPEG et JPEG2000. Les avantages de cette proposition optique est de pouvoir s appuyer sur les méthodes existantes très connues comme JPEG et JPEG2000. Les différents résultats obtenus (simulation et implantation optique) montrent bien qu il est tout à fait possible de réaliser la compression optiquement. Cette thèse montre aussi les avantages et les limitations que nous pouvons obtenir avec ce type des méthodes.The very fast increase in the use of images of very good quality in the fields of multimedia, computer games, satellite transmissions, medical imagery and digital cameras present two major problems: the transmission and storage of data. To gain in time as well as in memory, it is necessary to compress these images while keeping a good quality. However, in spite of the optical origin of the image, the process is often carried out digitally, which involves a loss of time related to the digitalization of this image before being able to apply the algorithm of the desired compression. Moreover, the digital compression of information becomes more complex and requires costly calculation time despite advances in information technology. This thesis deals with the problem of compression of fixed images, but from the optical implementation point of view in order to reduce die size of information by eliminating redundant information. The aim is to gain memory capacity along with faster transmission. Indeed, coherent optics makes it possible to carry out the transformation of a two dimensional image quasi instantaneously (for example die Fourier Transform). This property has been used for a long time to seek a particular object (target) in an unspecified scene (optical correlation technique). With the experience gained in our laboratory in the field of information optical processing, we have developed two methods of compression with an optical implementation adapted to JPEG and TPEG2000 standards. The advantage of these optical methods is that they are based on existing and well-known algorithms e.g. JPEG and JPEG2000. The various results obtained by simulation and their optical implementation really showed and convinced us tint it is possible to carry out optical image processing. This thesis also shows the advantages and limitations we can obtain with kind of methods.BREST-BU Droit-Sciences-Sports (290192103) / SudocSudocFranceF

Face Recognition Systems: A Survey

Over the past few decades, interest in theories and algorithms for face recognition has been growing rapidly. Video surveillance, criminal identification, building access control, and unmanned and autonomous vehicles are just a few examples of concrete applications that are gaining attraction among industries. Various techniques are being developed including local, holistic, and hybrid approaches, which provide a face image description using only a few face image features or the whole facial features. The main contribution of this survey is to review some well-known techniques for each approach and to give the taxonomy of their categories. In the paper, a detailed comparison between these techniques is exposed by listing the advantages and the disadvantages of their schemes in terms of robustness, accuracy, complexity, and discrimination. One interesting feature mentioned in the paper is about the database used for face recognition. An overview of the most commonly used databases, including those of supervised and unsupervised learning, is given. Numerical results of the most interesting techniques are given along with the context of experiments and challenges handled by these techniques. Finally, a solid discussion is given in the paper about future directions in terms of techniques to be used for face recognition

Highly Performing Automatic Detection of Structural Chromosomal Abnormalities Using Siamese Architecture

The detection of structural chromosomal abnormalities (SCA) is crucial for diagnosis, prognosis and management of many genetic diseases and cancers. This detection, done by highly qualified medical experts, is tedious and time-consuming. We propose a highly performing and intelligent method to assist cytogeneticists to screen for SCA. Each chromosome is present in two copies that make up a pair of chromosomes. Usually, SCA are present in only one copy of the pair. Convolutional neural networks (CNN) with Siamese architecture are particularly relevant for evaluating similarities between two images, which is why we used this method to detect abnormalities between both chromosomes of a given pair. As a proof-of-concept, we first focused on a deletion occurring on chromosome 5 (del(5q)) observed in hematological malignancies. Using our dataset, we conducted several experiments without and with data augmentation on seven popular CNN models. Overall, performances obtained were very relevant for detecting deletions, particularly with Xception and InceptionResNetV2 models achieving and of -score, respectively. We additionally demonstrated that these models successfully recognized another SCA, inversion inv(3), which is one of the most difficult SCA to detect. The performance improved when the training was applied on inversion inv(3) dataset, achieving of -score. The technique that we propose in this paper is the first highly performing method based on Siamese architecture that allows the detection of SCA. Our code is publicly available at: https://github.com/MEABECHAR/ChromosomeSiameseAD