Recognition of Object Categories in Realistic Scenes

Classification of images maps the image content into a certain semantic term such as categories, domain, object. Image classification should be able automatically check the existence of certain object (e.g. car, animal, and scene) in the image content. This task is still challenging in computer vision since we have to deal with the realistic image. The objective of this works is to discover the image classification methods by mixturing the existing techniques with the aim of the best results in classification. In this work, we implemented sparse coding method with spatial pyramid matching to classify the images. Beside gray SIFT, four SIFT color descriptors were also used as a local descriptor. Linear Super Vector Machine (SVM) is conducted for training and testing the images. The result of this work has shown that color descriptors improve significantly the classification rate compared to gray SIFT

Lipid Anti-Lipid Antibody Responses Correlate with Disease Activity in Systemic Lupus Erythematosus

10.1371/journal.pone.0055639PLoS ONE82

A comparison of profile changes between ramus and anterior mandibular subapical osteotomies in class III Chinese patients

Journal of Oral and Maxillofacial Surgery498831-837JOMS

Rétines à masques (utilisation de masques binaires pour l'implantation d'un opérateur de reconnaissance de forme dans une rétine CMOS)

Dans cette thèse nous proposons une méthode permettant implantable dans une rétine CMOS pour reconnaître une forme ou un objet. Elle est basée sur une mesure de corrélation entre une image analysée et une image binaire (masque) mémorisée dans la rétine. Une première approche, basée sur un seuillage de l'image de l'objet à reconnaître, a donné d'intéressants résultats mais reste sensible à la position de l'objet analysé. Une deuxième approche, utilisant le " dithering " pour générer le masque binaire, nous permet de mesurer la valeur des moments géométriques de l'image analysée, de déterminer la position de l'objet avant son analyse. Cette approche est innovante car elle conduit à une architecture de pixel simple et programmable. Les résultats obtenus ont été étendus à la mesure de moments de Legendre et de Zernike pour des applications de reconnaissance de formes et de compression d'images.In this thesis we propose a method that can be implemented in a CMOS retina for object or shape recognition. It is based on the measure of the correlation coefficient between the image under analysis and a binary image (mask) stored in memory devices in the retina. A first approach based on a simple thresholding of an image of the object to recognize has yielded interesting shape recognition results but it is sensitive to the position and orientation of the analyzed object. A second approach, using a dithering algorithm for, allows us to compute an estimated value of the geometrical moments of the analyzed image that are next used to determine the position of the object before its analysis. This approach is innovative since it is based on a novel, simple and programmable pixel architecture. Finally, the results obtained have been extended to the measurement of Legendre or Zernike moments for pattern recognition and image compression applications.DIJON-BU Sciences Economie (212312102) / SudocSudocFranceF

Esthetic arch bar for maxillomandibular fixation in orthognathic surgery.

Journal of esthetic dentistry4 Suppl35-3

Design of ADAS Fatigue Control System using Pynq z1 and Jetson Xavier NX

International audienc

Towards automatic analysis of ultrasonic time-of-flight diffraction data using genetic-based Inverse Hough Transform

International audienceUltrasonic Time Of Flight Diffraction (TOFD) is a non-destructive inspection technique that has proved to be very effective for the detection, localization and sizing of buried crack defects in steel structures. However, it produces huge amount of data that are manually processed and interpreted. This process is time-consuming and painstaking. Moreover, it requires the skill, alertness and experience of the operator. Consequently, it is subject to human errors. In order to save time, effort and inspection cost while at the same time increasing the detection rate, automatic analysis tool need to be developed. This paper presents thus an application of image processing techniques to the B-SCAN image representation of ultrasonic TOFD data so as to take advantage of the power of image representation of information. In a B-SCAN image crack defects are characterized by multiple arcs of diffraction. In order to detect these multiple arcs of diffraction and thus reveal the presence of a crack in the structure under inspection, some methods based on conventional Hough Transform (HT) were proposed in the literature. The main problems related to conventional HT are its large data storage requirements and expensive computation times. To cope with these problems, we propose the use of the Inverse Hough Transform (IHT) where the voting process is performed in the image space rather than the parameter space. With the IHT, the local peak detection problem in the parameter space is converted to a parameter optimization problem that is solved using Genetic Algorithms. The proposed Genetic-Based Inverse Voting Hough Transform ‘GBIVHT’ algorithm allows thus the automatic detection of the arcs of diffraction, and therefore the crack defects, while avoiding the computational complexity as well as the huge storage requirement of conventional HT

Application des techniques de numérisation tridimensionnelle au contrôle de process de pièces de forge

L objectif de ces travaux de thèse est la conception et le développement d un système de caractérisation tridimensionnelle de pièces forgées de grande dimension portées à haute température. Les travaux se basent sur de nombreuses thématiques telles que l acquisition tridimensionnelle, l extraction, la segmentation et le recalage de primitives 3D. Nous présentons tout d abord les limites des systèmes de caractérisation de pièces forgées cités dans la littérature. Dans la deuxième partie, nous présentons la réalisation du système de caractérisation de pièces forgées, constitué de deux scanners temps de vol (TOF). Nous présentons également le simulateur de numérisation par scanner TOF qui nous permet de nous affranchir des contraintes industrielles (temps, difficulté de manœuvres) pour positionner les deux scanners. La troisième partie est consacrée à l extraction des primitives 3D. Nous avons traité deux types de primitives : viroles et sphères avec deux approches différentes : méthode supervisée et méthode automatique. La première approche basée sur une méthode de croissance de région et de contour actif, permet d extraire des formes extrudées complexes. Des problèmes d ergonomie du système nous ont conduits à développer une deuxième approche, basée sur l image de Gauss et l extraction d ellipse, qui permet l extraction automatique de formes cylindriques ovales ou circulaires. Nous présentons également quatre méthodes d extraction automatique de sphères basées sur des approches heuristiques : RANSAC (RANdom SAmple Consensus), algorithme génétique et algorithme génétique par niche. Dans la quatrième partie, nous étudions les différentes approches de recalage de données 3D traitées : le calibrage basé sur les cibles artificielles et le recalage fin basé sur l algorithme ICP. Pour conclure, nous présentons la réalisation d un système complet de caractérisation tridimensionnelle de pièces forgées de grande dimension. Ensuite, nous comparons les performances et les limites de ce système avec les systèmes de caractérisation cités dans la littérature.The main objective of this Phd project is to conceive a machine vision system for hot cylindrical metallic shells diameters measurement during forging process. The manuscript is structured by developing in the first chapter the state of the art and the limits of hot metallic shells measurement systems suggested in literature. Our implemented system which is based on two conventional Time Of Flight (TOF) laser scanners has been described in the same chapter along, chapter two, with presentation of its respective numerical simulator. Simulation series have been done using the digitizing simulator and were aimed to determine the optimal positions of the two scanners without any industrial constraints (time, difficulty of operations). The third part of the manuscript copes with 3D primitives extraction. Two major types of approaches have been studied according to the primitive s form (cylinders or spheres) to be extracted: supervised method and automatic method. The first approach, based on a growing region method and active contour, enables to extract complex extruded forms; while problems of ergonomics have been solved using automatic methods that have been carried out along the programme research. The proposed methods consist in automatically extracting: oval or circular cylindrical forms, using Gauss map associated with ellipse extraction techniques : spherical forms, using heuristic approaches such as RANdom SAmple Consensus RANSAC, Genetic Algorithm (GA) and Niche Genetic Algorithm (NGA). Two varieties of 3D data registration approach have been presented and discussed in chapter 4: the registration based on the artificial targets and the fine registration based on algorithm ICP. A complete system for three-dimensional characterization of hot cylindrical metallic shells during forging process has been implemented and then compared with existing systems in order to identify its performances and limits in conclusion.DIJON-BU Doc.électronique (212319901) / SudocSudocFranceF

A CMOS Image Sensor Design for Speed Determination of Fast Moving Luminous Objects

International audienc

A Practical Calibration Method for RGB Micro-Grid Polarimetric Cameras

International audienc