Cette étude porte sur la mise en forme des matériaux composites renforcés par des fibres ou des mèches de fibres courtes tels que les SMC ou les BMC. Un travail expérimental a dans un premier temps été réalisé à l’échelle macroscopique. Ce travail a permis de mettre au point un rhéomètre de compression lubrifiée ainsi que des méthodes d’essais et de dépouillement. Ceci permet de mieux caractériser la rhéologie des compounds SMC et BMC en traitant les problématiques de leur compressibilité et des frottements éventuels entre les parois du rhéomètre et la matière déformée. Un travail numérique a ensuite permis de simuler la mise en forme d’un BMC après l’identification des paramètres d’un modèle rhéologique simple à partir des données expérimentales obtenues sur le rhéomètre. Enfin, un travail expérimental à l’échelle microscopique a permis d’une part de caractériser finement les microstuctures de SMC modèles à partir de microtomographies à rayons X, et d’autre part de caractériser et de modéliser par le biais d’essais d’extraction de fibres les interactions entre les mèches formant le renfort fibreux de ces matériaux. / This study focuses on the processing of composite materials reinforced with short fibres or fibres bundles such as SMC or BMC. Firstly, an experimental work was carried-out at the macroscopic scale. This work led to the development of a lubricated compression rheometer and associated analysis methods to better characterize the rheology of SMC and BMC compounds, by accounting for the compressibility of compounds and the possible friction between the rheometer wall and the flowing composite. Numerical simulation was then achieved in order to simulate the forming of a BMC. For that purpose, the constitutive parameters of a simple tensorial rheological model were determined from experimental data obtained with the rheometer. Finally, an experimental work at the microscopic level allowed (i) the microstuctures of SMC models from X-ray microtomography micrographs and (ii) fibre pull-out experiment to be characterized, and the interaction mechanisms between the fiber bundles forming the fiber reinforcement of these materials to be modelled.

Made available in DSpace on 2014-12-17T14:58:15Z (GMT). No. of bitstreams: 1 MayaraSCFL_DISSERT.pdf: 5165682 bytes, checksum: c5b249c3b897f27db4e517452be9b9ce (MD5) Previous issue date: 2012-04-30 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Composites based on PEEK + PTFE + CARBON FIBER + Graphite (G_CFRP) has increased application in the top industries, as Aerospace, Aeronautical, Petroleum, Biomedical, Mechanical and Electronics Engineering challenges. A commercially available G_CFRP was warmed up to three different levels of thermal energy to identify the main damage mechanisms and some evidences for their intrinsic transitions. An experimental test rig for systematize a heat flux was developed in this dissertation, based on the Joule Effect. It was built using an isothermal container, an internal heat source and a real-time measurement system for test a sample by time. A standard conical-cylindrical tip was inserted into a soldering iron, commercially available and identified by three different levels of nominal electrical power, 40W (manufacturer A), 40W (manufacturer B), 100W and 150W, selected after screening tests: these power levels for the heat source, after one hour of heating and one hour of cooling in situ, carried out three different zones of degradation in the composite surface. The bench was instrumented with twelve thermocouples, a wattmeter and a video camera. The twelve specimens tested suffered different degradation mechanisms, analyzed by DSC (Differential Scanning Calorimetry) and TG (Thermogravimetry) techniques, Scanning Electron Microscopy (SEM) and Energy-Dispersive X-Rays (EDX) Analysis. Before and after each testing, it was measured the hardness of the sample by HRM (Hardness Rockwell M). Excellent correlations (R2=1) were obtained in the plots of the evaporated area after one hour of heating and one hour of cooling in situ versus (1) the respective power of heat source and (2) the central temperature of the sample. However, as resulting of the differential degradation of G_CFRP and their anisotropy, confirmed by their variable thermal properties, viscoelastic and plastic properties, there were both linear and non-linear behaviour between the temperature field and Rockwell M hardness measured in the radial and circumferential directions of the samples. Some morphological features of the damaged zones are presented and discussed, as, for example, the crazing and skeletonization mechanism of G_CFRP / Comp?sitos baseados em matrizes polim?ricas de PEEK e PTFE, refor?adas com fibra de carbono e grafite (G_CFRP) apresentam crescente aplica??o e desafios ? Engenharia nas ind?strias Aeroespacial, Aeron?utica, de Petr?leo, Biom?dica, Mec?nica e Eletr?nica. Um comp?sito G_CFRP foi aquecido em tr?s n?veis de energia t?rmica para identificar os principais mecanismos de dano e algumas evid?ncias em suas transi??es de mecanismos. Uma bancada experimental foi desenvolvida para sistematizar o fluxo t?rmico com base no Efeito Joule. Foi constru?da usando-se um recipiente isot?rmico, uma fonte quente interna e um sistema de medidas em tempo real para ensaiar um corpo-de-prova (CP) de cada vez. Uma ponta c?nica-cil?ndrica foi inserida em um ferro de soldar, comercialmente dispon?vel e identificado por tr?s diferentes n?veis de pot?ncia el?trica, 40W (fabricante A), 40W (fabricante B), 100W e 150W, selecionados ap?s ensaios piloto: estes n?veis de pot?ncia para a fonte quente, ap?s uma hora de aquecimento e uma hora de resfriamento in situ, promoveu tr?s zonas diferentes de degrada??o na superf?cie do comp?sito. A bancada foi instrumentada com doze termopares, um watt?metro e uma c?mera de v?deo. Os doze C.P. ensaiados apresentaram diferentes mecanismos de degrada??o, analisados pelas t?cnicas de Calorimetria Diferencial Explorat?ria (DSC) e Termogravimetria (TG), e pelas an?lises de Microscopia Eletr?nica de Varredura (MEV) e Energia Dispersiva de Raios-X (EDS). Antes e ap?s cada ensaio, foram feitos ensaios de dureza Rockwell M (HRM). Excelentes correla??es (R2=1) foram obtidas nas curvas da ?rea evaporada ap?s uma hora de aquecimento e uma hora de resfriamento in situ versus (1) a respectiva pot?ncia da fonte quente e (2) a temperatura central do C.P. entretanto, como resultado da degrada??o diferencial do G_CFRP e da sua anisotropia, confirmadas por suas propriedades t?rmicas vari?veis, propriedades viscoel?sticas e viscopl?sticas, houve comportamentos linear e n?o-linear entre o campo de temperatura e a HRM medidos nas dire??es radial e circunferencial dos C.P. Algumas peculiaridades morfol?gicas das zonas de dano s?o apresentadas e discutidas, como, por exemplo, os mecanismos de dano por crazing e esqueletiza??o do G_CFRP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The handwritten signature is a form of personal identification widely accepted, both socially and legally, used for centuries to authenticate documents such as bank checks, letters, contracts and any type of service that requires proof of authorship. When signing, an individual inserts a large amount of information to transform the movement of his hand into an identifying element. Writing speed, trajectory traversed, pen inclination, applied pressure, all these data are articulated (in the form of latent variables) to result in a static figure in the signed document. This dissertation investigates the problem of trajectory extraction of the pen that generates this signature from the resulting static image. For this, the work was divided in three main steps that are: (i) compute the skeleton of the offline signature; (ii) extract its characteristics using a concept addressed in this work called UCSS, and, with the help of previously recorded online signatures, (iii) estimate the path that the pen traveled over the skeleton. In each of these steps, a review of relevant work on the themes was done prior to begin implementation. Three experiments were carried out during this work, the first one was done with the objective of comparing the results obtained with the developed algorithm and the results obtained in a reference work, the other two were realized during the production of an article destined to the publication attached to this job. / A assinatura manuscrita é uma forma de identificação pessoal amplamente aceita, tanto social como juridicamente, utilizada há séculos para autenticar documentos como cheques bancários, cartas, contratos e todo tipo de serviço que necessite prova de autoria. Ao assinar, um indivíduo insere uma grande quantidade de informação para transformar o movimento de sua mão em um elemento identificador. Velocidade de escrita, trajetória percorrida, inclinação da caneta, pressão aplicada, todos esses dados são articulados (na forma de variáveis latentes) para resultar em uma figura estática no documento assinado. Essa dissertação investiga o problema de extração de trajetória da caneta que gera essa assinatura a partir da imagem estática resultante. Para isso, o trabalho foi divido em três passos principais que são: (i) computar o esqueleto da assinatura offline; (ii) extrair suas características utilizando um conceito abordado neste trabalho chamado UCSS, e, com o auxílio de assinaturas online registradas previamente; (iii) estimar o caminho que a caneta percorreu sobre o esqueleto. Em cada um desses passos, foi feita uma revisão de trabalhos relevantes sobre os temas para só então iniciar as implementações. Foram realizados três experimentos durante este trabalho, o primeiro foi feito com o objetivo de comparar os resultados obtidos com o algoritmo desenvolvido e os resultados obtidos em um trabalho de referência, os outros dois foram realizados durante a produção de um artigo destinado a publicação anexado a este trabalho.

L’opération morphologique de squelettisation transforme chaque objet d’une image en une forme linéique qui préserve la topologie de ce dernier (propriété d’homotopie). Elle est largement utilisée en biométrie mais aussi dans la reconnaissance des caractères ainsi que pour l’extraction de la microarchitecture osseuse. L’objectif de cette thèse est de développer une méthode de squelettisation appliquée directement sur les niveaux de gris de l’image, ce qui a pour large avantage de s’affranchir de prétraitement comme la binarisation. Une revue des méthodes de squelettisation en niveaux de gris permet de constater que l’amincissement est l’une des approches les plus usitées de par sa propriété d’homotopie. Cependant, cette approche est sensible au bruit de l’image et produit des squelettes sur-connectés. Un premier paramétrage de l’amincissement a été proposé dans la littérature afin d’abaisser des configurations de pixels liées au bruit. La première contribution de ce travail est de proposer un ajustement de ce paramètre basé sur une décision statistique. Il s’agit d’identifier les tests d’hypothèses correspondants aux différentes configurations d’abaissement en vue de fixer ce paramètre de façon locale. Ceci conduit à la mise en place d’une squelettisation appelée Self Contrast Controlled Thinning (SCCT) puisque robuste au bruit tout en s’adaptant automatiquement au contraste de l’image. La squelettisation SCCT est rendue accessible aux domaines d’application grâce à son implantation optimisée basée sur les files d’attente hiérarchiques. Ayant noté le peu d’efforts consacrés à l’évaluation de la squelettisation en niveaux de gris, la deuxième contribution de ce travail est de proposer un protocole visant à évaluer l’opération de squelettisation sur la base des propriétés requises à savoir la préservation de la topologie et de la géométrie. Ce protocole est déroulé sur une base d’images synthétiques et nous permet de comparer notre approche à celles de la littérature. La troisième contribution est de proposer une structuration du squelette en graphe donnant accès aux descripteurs structurels et morphométriques des objets étudiés en vue d’une exploitation du squelette par les experts des domaines d’applications. Dans le cadre du projet Voxelo coordonné par le laboratoire B2OA de l’Université Paris Diderot, cette structuration est exploitée pour extraire les descripteurs de la qualité de la microarchitecture osseuse à partir d’images RX haute résolution. / Skeletonization is an image transformation that aims to represent objects by their medial axis while preserving their topological characteristics (homotopy). It is widely used in biometrics, character recognition and also in the extraction of bone microarchitecture. The objective of this thesis is to develop a skeletonization method applied directly on image gray levels. This has the large advantage of freeing the operation from preprocessing techniques such as binarization. A review of grayscale skeletonization methods shows that the morphological thinning is one of the most used approaches for its topology preservation property. However, this approach is sensitive to image noise and produces inexploitable skeletons. A first parameterization of the thinning process has been proposed in the literature to reduce noise-related information. The first contribution of this work is to propose an adjustment of this parameter based on a statistical decision. To this end, a hypothesis test is identified for each lowering criterion in order to set the thinning parameter locally. This leads us to propose the Self Contrast Controlled Thinning method SCCT that is robust to noise and is automatically adjusted to image contrast. The SCCT is made available to application domains through its optimized implementation based on hierarchical queues. Noticing the lack of efforts to assess grayscale skeletonization, the second contribution of this work is to propose a quantitative evaluation protocol assessing skeletonization with regard to its fundamental properties that are namely the preservation of topology and geometry. This protocol is conducted over a synthetic images database and allows us to compare SCCT to approaches from the literature. The third contribution consists in structuring the skeleton into a graph that gives access to objects structural and morphometric descriptors and enables the exploitation of the skeleton by experts from various fields of application. This structuring is applied in the context of Voxelo project which is coordinated by B2OA laboratory of the University Paris Diderot. In this context, descriptors of bone microarchitecture quality are extracted from X-ray high resolution images.

Des efforts de recherche considérables ont été déployés afin d'améliorer les résultats de traitement de cancers pulmonaires. L'étude de la déformation de l'anatomie du patient causée par la ventilation pulmonaire est au coeur du processus de planification de traitement radio-oncologique. À l'aide d'images de tomodensitométrie quadridimensionnelles (4DCT), une simulation dosimétrique peut être calculée sur les 10 ensembles d'images du 4DCT. Une méthode doit être employée afin de recombiner la dose de radiation calculée sur les 10 anatomies représentant une phase du cycle respiratoire. L'utilisation de recalage déformable d'images (DIR), une méthode de traitement d'images numériques, génère neuf champs vectoriels de déformation permettant de rapporter neuf ensembles d'images sur un ensemble de référence correspondant habituellement à la phase d'expiration profonde du cycle respiratoire. L'objectif de ce projet est d'établir une méthode de génération de champs de déformation à l'aide de la DIR conjointement à une méthode de validation de leur précision. Pour y parvenir, une méthode de segmentation automatique basée sur la déformation surfacique de surface à été créée. Cet algorithme permet d'obtenir un champ de déformation surfacique qui décrit le mouvement de l'enveloppe pulmonaire. Une interpolation volumétrique est ensuite appliquée dans le volume pulmonaire afin d'approximer la déformation interne des poumons. Finalement, une représentation en graphe de la vascularisation interne du poumon a été développée afin de permettre la validation du champ de déformation. Chez 15 patients, une erreur de recouvrement volumique de 7.6 ± 2.5[%] / 6.8 ± 2.1[%] et une différence relative des volumes de 6.8 ± 2.4 [%] / 5.9 ± 1.9 [%] ont été calculées pour le poumon gauche et droit respectivement. Une distance symétrique moyenne 0.8 ± 0.2 [mm] / 0.8 ± 0.2 [mm], une distance symétrique moyenne quadratique de 1.2 ± 0.2 [mm] / 1.3 ± 0.3 [mm] et une distance symétrique maximale 7.7 ± 2.4 [mm] / 10.2 ± 5.2 [mm] ont aussi été calculées pour le poumon gauche et droit respectivement. Finalement, 320 ± 51 bifurcations ont été détectées dans le poumons droit d'un patient, soit 92 ± 10 et 228 ± 45 bifurcations dans la portion supérieure et inférieure respectivement. Nous avons été en mesure d'obtenir des champs de déformation nécessaires pour la recombinaison de dose lors de la planification de traitement radio-oncologique à l'aide de la méthode de déformation hiérarchique des surfaces. Nous avons été en mesure de détecter les bifurcations de la vascularisation pour la validation de ces champs de déformation. / Purpose: To allow a reliable deformable image registration (DIR) method for dose calculation in radiation therapy and to investigate an automatic vessel bifurcations detection algorithm for DIR assessment to improve lung cancer radiation treatment. Methods: 15 4DCT datasets are acquired and deep exhale respiratory phases are exported to Varian treatment planning system (TPS) Eclipse^{\text{TM}} for contouring. Voxelized contours are smoothed by a Gaussian filter and then transformed into a surface mesh representation. Such mesh is adapted by rigid and elastic deformations based on hierarchical surface deformation to match each subsequent lung volumes. The segmentation efficiency is assessed by comparing the segmented lung contour and the TPS contour considering two volume metrics, defined as Volumetric Overlap Error (VOE) [%] and Relative Volume Difference (RVD) [%] and three surface metrics, defined as Average Symmetric Surface Distance (ASSD) [mm], Root Mean Square Symmetric Surface Distance (RMSSD) [mm] and Maximum Symmetric Surface Distance (MSSD) [mm]. Vesselness filter was applied within the segmented lung volumes to identify blood vessels and airways. Segmented blood vessels and airways were skeletonised using a hierarchical curve-skeleton algorithm based on a generalized potential field approach. A graph representation of the computed skeleton was generated to assign one of three labels to each node: the termination node, the continuation node or the branching node. Results: The volume metrics obtained are a VOE of 7.6 ± 2.5[%] / 6.8 ± 2.1[%] and a RVD of 6.8 ± 2.4 [%] / 5.9 ± 1.9 [%] respectively for left and right lung. The surface metrics computed are an ASSD of 0.8 ± 0.2 [mm] / 0.8 ± 0.2 [mm], a RMSSD of 1.2 ± 0.2 [mm] / 1.3 ± 0.3 [mm] and a MSSD of 7.7 ± 2.4 [mm] / 10.2 ± 5.2 [mm] respectively for left and right lung. 320 ± 51 bifurcations were detected in the right lung of a patient for the 10 breathing phases. 92 ± 10 bifurcations were found in the upper half of the lung and 228 ± 45 bifurcations were found in the lower half of the lung. Discrepancies between ten vessel trees were mainly ascribed to the segmentation methode. Conclusions: This study shows that the morphological segmentation algorithm can provide an automatic method to capture an organ motion from 4DCT scans and translate it into a volume deformation grid needed by DIR method for dose distribution combination. We also established an automatic method for DIR assessment using the morphological information of the patient anatomy. This approach allows a description of the lung’s internal structure movement, which is needed to validate the DIR deformation fields.

No description available.

Tesis por compendio / [ES] El objetivo principal de esta tesis es el desarrollo de técnicas avanzadas de seguimiento de posturas para reconocimiento de comportamientos del Caenorhabditis elegans o C. elegans. El C. elegans es una clase de nematodo utilizado como organismo modelo para el estudio y tratamientos de diferentes enfermedades patológicas así como neurodegenerativas. Su comportamiento ofrece información valiosa para la investigación de nuevos fármacos (o productos alimenticios y cosméticos saludables) en el estudio de lifespan y healthspan. Al día de hoy, muchos de los ensayos con C. elegans se realizan de forma manual, es decir, usando microscopios para seguirlos y observar sus comportamientos o en laboratorios más modernos utilizando programas específicos. Estos programas no son totalmente automáticos, requieren ajuste de parámetros. Y en otros casos, son programas para visualización de imágenes donde el operador debe etiquetar maualmente el comportamiento de cada C. elegans. Todo esto se traduce a muchas horas de trabajo, lo cual se puede automatizar utilizando técnicas de visión por computador. Además de poder estimar indicadores de movilidad con mayor precisión que un operador humano. El problema principal en el seguimiento de posturas de C. elegans en placas de Petri son las agregaciones entre nematodos o con ruido del entorno. La pérdida o cambios de identidad son muy comunes ya sea de forma manual o usando programas automáticos/semi-automáticos. Y este problema se vuelve más complicado aún en imágenes de baja resolución. Los programas que automatizan estas tareas de seguimiento de posturas trabajan con técnicas de visión por computador usando técnicas tradicionales de procesamiento de imágenes o técnicas de aprendizaje profundo. Ambas técnicas han demostrado excelentes resultados en la detección y seguimiento de posturas de C. elegan}. Por un lado, técnicas tradicionales utilizan algoritmos/optimizadores para obtener la mejor solución, mientras que las técnicas de aprendizaje profundo aprenden de forma automática características del conjunto de datos de entrenamiento. El problema con las técnicas de aprendizaje profundo es que necesitan un conjunto de datos dedicado y grande para entrenar los modelos. La metodología utilizada para el desarrollo de esta tesis (técnicas avanzadas de seguimiento de posturas) se encuadran dentro del área de investigación de la visión artificial. Y ha sido abordada explorando ambas ramas de visión por computador para resolver los problemas de seguimiento de posturas de C. elegans en imágenes de baja resolución. La primera parte, es decir, secciones 1 y 2, capítulo 2, utilizó técnicas tradicionales de procesamiento de imágenes para realizar la detección y seguimiento de posturas de los C. elegans. Para ello se propuso una nueva técnica de esqueletización y dos nuevos criterios de evaluación para obtener mejores resultados de seguimiento, detección, y segmentación de posturas. Las siguientes secciones del capítulo 2 utilizan técnicas de aprendizaje profundo, y simulación de imágenes sintéticas para entrenar modelos y mejorar los resultados de detección y predicción de posturas. Los resultados demostraron ser más rápidos y más precisos en comparación con técnicas tradicionales. También se demostró que los métodos de aprendizaje profundo son más robustos ante la presencia de ruido en la placa. / [CA] L'objectiu principal d'aquesta tesi és el desenvolupament de tècniques avançades de seguiment de postures per a reconeixement de comportaments del Caenorhabditis elegans o C. elegans. El C. elegans és una classe de nematodo utilitzat com a organisme model per a l'estudi i tractaments de diferents malalties patològiques així com neurodegeneratives. El seu comportament ofereix informació valuosa per a la investigació de nous fàrmacs (o productes alimentosos i cosmètics saludables) en l'estudi de lifespan i healthspan. Al dia de hui, molts dels assajos amb C. elegans es realitzen de manera manual, és a dir, usant microscopis per a seguir-los i observar els seus comportaments o en laboratoris més moderns utilitzant programes específics. Aquests programes no són totalment automàtics, requereixen ajust de paràmetres. I en altres casos, són programes per a visualització d'imatges on l'operador ha d'etiquetar maualment el comportament de cada C. elegans. Tot això es tradueix a moltes hores de treball, la qual cosa es pot automatitzar utilitzant tècniques de visió per computador. A més de poder estimar indicadors de mobilitat amb major precisió que un operador humà. El problema principal en el seguiment de postures de C. elegans en plaques de Petri són les agregacions entre nematodes o amb soroll de l'entorn. La pèrdua o canvis d'identitat són molt comuns ja siga de manera manual o usant programes automàtics/semi-automàtics. I aquest problema es torna més complicat encara en imatges de baixa resolució. Els programes que automatitzen aquestes tasques de seguiment de postures treballen amb tècniques de visió per computador usant tècniques tradicionals de processament d'imatges o tècniques d'aprenentatge profund. Totes dues tècniques han demostrat excel·lents resultats en la detecció i seguiment de postures de C. elegans. D'una banda, tècniques tradicionals utilitzen algorismes/optimizadors per a obtindre la millor solució, mentre que les tècniques d'aprenentatge profund aprenen de manera automàtica característiques del conjunt de dades d'entrenament. El problema amb les tècniques d'aprenentatge profund és que necessiten un conjunt de dades dedicat i gran per a entrenar els models. La metodologia utilitzada per al desenvolupament d'aquesta tesi (tècniques avançades de seguiment de postures) s'enquadren dins de l'àrea d'investigació de la visió artificial. I ha sigut abordada explorant totes dues branques de visió per computador per a resoldre els problemes de seguiment de postures de C. elegans en imatges de baixa resolució. La primera part, és a dir, secció 1 i 2, capítol 2, va utilitzar tècniques tradicionals de processament d'imatges per a realitzar la detecció i seguiment de postures dels C. elegans. Per a això es va proposar una nova tècnica de esqueletizació i dos nous criteris d'avaluació per a obtindre millors resultats de seguiment, detecció i segmentació de postures. Les següents seccions del capítol 2 utilitzen tècniques d'aprenentatge profund i simulació d'imatges sintètiques per a entrenar models i millorar els resultats de detecció i predicció de postures. Els resultats van demostrar ser més ràpids i més precisos en comparació amb tècniques tradicionals. També es va demostrar que els mètodes d'aprenentatge profund són més robustos davant la presència de soroll en la placa. / [EN] The main objective of this thesis is the development of advanced posture-tracking techniques for behavioural recognition of Caenorhabditis elegans or C. elegans. C. elegans is a kind of nematode used as a model organism for the study and treatment of different pathological and neurodegenerative diseases. Their behaviour provides valuable information for the research of new drugs (or healthy food and cosmetic products) in the study of lifespan and healthspan. Today, many of the tests on C. elegans are performed manually, i.e. using microscopes to track them and observe their behaviour, or in more modern laboratories using specific software. These programmes are not fully automatic, requiring parameter adjustment. And in other cases, they are programmes for image visualisation where the operator must label the behaviour of each C. elegans manually. All this translates into many hours of work, which can be automated using computer vision techniques. In addition to being able to estimate mobility indicators more accurately than a human operator. The main problem in tracking C. elegans postures in Petri dishes is aggregations between nematodes or with noise from the environment. Loss or changes of identity are very common either manually or using automatic/semi-automatic programs. And this problem becomes even more complicated in low-resolution images. Programs that automate these pose-tracking tasks work with computer vision techniques using either traditional image processing techniques or deep learning techniques. Both techniques have shown excellent results in the detection and tracking of C. elegans postures. On the one hand, traditional techniques use algorithms/optimizers to obtain the best solution, while deep learning techniques automatically learn features from the training dataset. The problem with deep learning techniques is that they need a dedicated and large dataset to train the models. The methodology used for the development of this thesis (advanced posture-tracking techniques) falls within the research area of computer vision. It has been approached by exploring both branches of computer vision to solve the posture-tracking problems of C. elegans in low-resolution images. The first part, i.e. sections 1 and 2, chapter 2, used traditional image processing techniques to perform posture detection and tracking of C. elegans. For this purpose, a new skeletonization technique and two new evaluation criteria were proposed to obtain better posture-tracking, detection, and segmentation results. The next sections of chapter 2 use deep learning techniques, and synthetic image simulation to train models and improve posture detection and prediction results. The results proved to be faster and more accurate compared to traditional techniques. Deep learning methods were also shown to be more robust in the presence of plate noise. / This research was supported by Ministerio de Ciencia, Innovación y Universidades [RTI2018-094312-B-I00 (European FEDER funds); FPI PRE2019-088214], and also was supported by Universitat Politècnica de València [“Funding for open access charge: Uni- versitat Politècnica de València”]. The author received a scholarship from the grant: Ayudas para contratos predoctorales para la formación de doctores 2019. / Layana Castro, PE. (2023). Desarrollo de técnicas avanzadas de seguimiento de posturas para reconocimiento de comportamientos de C. elegans [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/198879 / Compendio