A. Diou’s research while affiliated with University of Burgundy and other places

A numerical model is presented in order to modelize the bright ring that appears in backlit optical shadowgraphy on a transparent hollow sphere with a solid deuterium-tritium layer inside. This novel model is based on computational calculations applied to the problem of the targets used in inertial confinement fusion. The model takes into account the influences of the optical imaging system (numerical aperture, source divergence, camera resolution, etc.) and the effect of the capsule itself, diameter, thickness, and refractive index, and allows one to analyze the inner surface of a capsule in terms of thickness and roughness.

Scanning techniques combining laser line projection with motion are simple and efficient. But there are number of cases in which laser triangulation fails. Some have well known solutions. Other, like adverse illumination by intense white light or presence of textures make laser projection hard to distinguish, and have no specific solution. In this article, a method is presented to improve retrieving laser projection for those cases. It"s build upon two main ideas. First, using auxiliary lines to create local high frequencies. Second, Transform a high speed camera in an intensity modulation receiver. The principle is to send a periodic message in the lines intensity and try to track traces of a spatial-temporal deforming pattern in the video sequences produced by the camera. It permits two main improvements. First, when adverse illumination produce other lines, they can be discriminate by the fact they don"t send the message. Second, when adverse illumination produce a highly luminous image or when a texture diffuse a part of the laser energy, it"s sufficient to track the noise of the message. By choosing a message, it"s possible to create every type of noise in order to distinguish it between the rest of image noises.

In this paper we propose a Genetic-Based Inverse Voting Hough Transform (GBIVHT) method for detecting parabolic shapes iii B-scan images obtained by the ultrasonic Time Of Flight Diffraction inspection technique. These parabolic shapes are characteristics of the presence of crack defects in the engineering structure under inspection. In our method, the local peak detection problem in the parameters space of conventional Hough Transform is converted into a parameter optimization problem that operates directly on the ultrasound B-scan image. The optimization is done using the well-known Genetic Algorithms. Our main goals are an accurate detection of the parabolas while circumventing the computational complexity and huge storage problem tied to conventional Hough Transform.

We present a method for calibrating a range finder system composed of a camera and a structured light source. The system is used to reconstruct the three-dimensional (3-D) surface of an object. This is achieved by projecting a pattern, represented by a set of regularly spaced spots, on the surface of the object using the structured light source. An image of the illuminated object is next taken and by analyzing the distortion of the projected pattern, the 3-D surface of the object can be reconstructed. This reconstruction operation can be envisaged only if the system is calibrated. Instead of using a classical calibration method, which is based on the determination of the matrices that characterize the intrinsic and extrinsic parameters of the system, we propose a fast and easy to set up methodology, consisting of taking a sequence of images of a plane in translation on which a set of regularly spaced spots is projected using the structured light projection system. Next, a relationship between the position of the plane and the coordinates of the spots in the image is established. Using this relationship, we are able to determine the 3-D coordinates of a set of points on the object's surface knowing the 2-D coordinates of the spots in the image of the object taken by the range finder system. Finally, from the 3-D coordinates of the set of points, the 3-D surface of the object is reconstructed.

We propose a genetic-based inverse voting Hough transform (GBIVHT) method to detect buried crack defects in engineering structures. The method is applied to B-scan images obtained according to the ultrasonic time of flight diffraction technique. In these image representations of the ultrasound data, crack defects are characterized by multiple arcs of diffraction that can be approximated by a parabolic model. Thus, the crack defect detection problem in non-destructive inspection of engineering structures is transformed into a parabola detection and localization on B-scan images. In the proposed GBIVHT method, the local peak detection problem of conventional HT is converted into a parameter optimization problem that operates directly on the B-scan images. The optimization task is done using the well-known genetic algorithms. Our main goals are an accurate detection of the parabolas while circumventing the computational complexity and huge storage problem tied to conventional HT.

We propose a genetic-based inverse voting Hough (1962) transform (GBIVHT) method for detecting parabolic shapes in B-scan images obtained by the ultrasonic time of flight diffraction inspection technique. These parabolic shapes are characteristics of the presence of crack defects in the engineering structure under inspection. In our method, the local peak detection problem in the parameters space of the conventional Hough transform is converted into a parameter optimization problem that operates directly on the ultrasound B-scan image. The optimization is done using the well-known genetic algorithms. Our main goals are an accurate detection of the parabolas while circumventing the computational complexity and huge storage problem tied to conventional Hough transform.

A new image-processing approach for object analysis in life and earth sciences is presented. This approach is based on a multiresolution algorithm in image processing. A clamshell surface has been digitized using a noncontact optical sensor based on laser triangulation. The 3D surface obtained constitutes an image that can be characterized by multiresolution analysis. The application of this method to the study of a bivalve shell surface (Unio sp., Recent Atlantic, Holocene) allowed the various growth increments and their potential relationship with environmental constraints to be measured. The algorithm used in this paper is based on the wavelet transform theory.

Shell increments contain information related to the evolution of the environment in which the organism grew during its biomineralization. To extract the information from variations in shell topography, a new and promising technique is presented, involving multi-scale analysis of the shell topography using a B-spline wavelet transform. An accurate non-contact optical system, based on laser triangulation, is used to map the shell surface. The resulting range image is treated as a grey-level image by using a multi-resolution approach based on the generalization of the cascade algorithm. This method allows reconstruction of non-subsampled images that correspond to the projection onto the space of the chosen scale of detail. This new approach provides an efficient tool for analyzing multi-scale information contained in growth increment rings and/or within quasi-periodic features. In conclusion, this approach can be applied to any 3D object, in order to extract features such as rhythmic information, color variations or object envelope.

The increasing popularity of the field programmable gate array (FPGA) has generated a great deal of interest for FPGA design problems. Due to the fact that FPGAs are mainly characterized both by high integration rate and “reprogrammability”, they are useful for complex image processing. However, fast processing is not possible without parallel processing; also traditional integration methods are not sufficient enough. Thus, one possible way is to adapt the processing algorithm to the FPGA architecture and to avoid general methods of schematic description, allowing an easily implantation, but not an optimum partitioning-routing. With this aim, we tried to minimize the number of CLBs (configurable logic block) in the FPGA, to integrate logical functions (addition, multiplication, comparison etc.) dedicated to segmentation, classification, as well as filtering operations. This is done by expressing the whole “architecture-function to integrate” as Boolean constraints

Ultrasonic non-destructive inspection is today widely employed in industry for detecting embedded or surface defects in engineering structures. However, the processing of data from ultrasonic inspection is rarely automated. The objective of our study is to develop a data processing system which makes use of image processing techniques in order to assist the ultrasonic inspection operator in his difficult task. The research work described has thus been done with this objective in mind and it concerns a method that we have developed for the automatic detection and characterization of defects. This method is based on the Hough transform and it allows one to localize defects in the component under inspection. By an automatic analysis of the “ultrasonic” data. The defects that are considered are tiny cracks in thick metallic structures