Détermination automatique du seuil de binarisation des modules des gradients par modélisation de leur histogramme

National audienceThis paper presents an enhanced method of image thresholding presented in [6]. The goal is to obtain the edges of objects in an image using a gradient magnitude histogram to automatically determine the threshold value. The method must be simple to be fast and easy to implement on an FPGA circuit. The computed edges will be used within a 3D perception task for high-speed machining security.Nous présentons dans cette communication une amélioration d'une méthode présentée dans [6]. Notre objectif est d'obtenir les contours dans une image à partir de la binarisation des modules des gradients. Ces contours sont obtenus à partir d'un seuil calculé automatiquement sur l'histogramme du module des gradients. La méthode doit être simple pour être rapide, implantable sur un circuit FPGA, et doit exploiter les gradients calculés par ailleurs. La méthode sera intégrée dans une tâche de perception 3D pour la vérification de montage d'usinage en vue de sécuriser l'opération d'usinage grande vitesse

Edge Detection via Edge-Strength Estimation Using Fuzzy Reasoning and Optimal Threshold Selection Using Particle Swarm Optimization

An edge is a set of connected pixels lying on the boundary between two regions in an image that differs in pixel intensity. Accordingly, several gradient-based edge detectors have been developed that are based on measuring local changes in gray value; a pixel is declared to be an edge pixel if the change is significant. However, the minimum value of intensity change that may be considered to be significant remains a question. Therefore, it makes sense to calculate the edge-strength at every pixel on the basis of the intensity gradient at that pixel point. This edge-strength gives a measure of the potentiality of a pixel to be an edge pixel. In this paper, we propose to use a set of fuzzy rules to estimate the edge-strength. This is followed by selecting a threshold; only pixels having edge-strength above the threshold are considered to be edge pixels. This threshold is selected such that the overall probability of error in identifying edge pixels, that is, the sum of the probability of misdetection and the probability of false alarm, is minimum. This minimization is achieved via particle swarm optimization (PSO). Experimental results demonstrate the effectiveness of our proposed edge detection method over some other standard gradient-based methods

2D and 3D surface image processing algorithms and their applications

This doctoral dissertation work aims to develop algorithms for 2D image segmentation application of solar filament disappearance detection, 3D mesh simplification, and 3D image warping in pre-surgery simulation. Filament area detection in solar images is an image segmentation problem. A thresholding and region growing combined method is proposed and applied in this application. Based on the filament area detection results, filament disappearances are reported in real time. The solar images in 1999 are processed with this proposed system and three statistical results of filaments are presented. 3D images can be obtained by passive and active range sensing. An image registration process finds the transformation between each pair of range views. To model an object, a common reference frame in which all views can be transformed must be defined. After the registration, the range views should be integrated into a non-redundant model. Optimization is necessary to obtain a complete 3D model. One single surface representation can better fit to the data. It may be further simplified for rendering, storing and transmitting efficiently, or the representation can be converted to some other formats. This work proposes an efficient algorithm for solving the mesh simplification problem, approximating an arbitrary mesh by a simplified mesh. The algorithm uses Root Mean Square distance error metric to decide the facet curvature. Two vertices of one edge and the surrounding vertices decide the average plane. The simplification results are excellent and the computation speed is fast. The algorithm is compared with six other major simplification algorithms. Image morphing is used for all methods that gradually and continuously deform a source image into a target image, while producing the in-between models. Image warping is a continuous deformation of a: graphical object. A morphing process is usually composed of warping and interpolation. This work develops a direct-manipulation-of-free-form-deformation-based method and application for pre-surgical planning. The developed user interface provides a friendly interactive tool in the plastic surgery. Nose augmentation surgery is presented as an example. Displacement vector and lattices resulting in different resolution are used to obtain various deformation results. During the deformation, the volume change of the model is also considered based on a simplified skin-muscle model

Through-Life Monitoring of the impact of vibration on the reliability of area array packages using Non- Destructive Testing

In order to keep up with the demands for faster, cheaper and smaller electronics, the packaging industry has evolved tremendously. Area array packages like flip chips and ball grid arrays are therefore widely used in modern day electronics. However, from the reliability standpoint, solder joints in these area array packages are often the weakest link. In case of harsh vibration environments like military and automobile applications, joint failure mainly occurs due to the high stress incurred during extreme environmental conditions that lead to fatigue failures. This thesis aims to study the effects of real time vibration on area array packages (flip chips in particular) using acoustic micro imaging for through life monitoring of the solder joints. Since real time vibration on solder joints have not been studied before, the various steps for successful testing, through life monitoring of the solder joints and data analysis will be investigated and discussed. Based on automobile industry standards, a real time vibration profile was obtained with the help of Delphi experts, who are the industry collaborators of this project. Due to its strong capability to detect discontinuities within materials and interconnections, Acoustic Micro Imaging (AMI) also known as Scanning Acoustic Microscopy (CSAM) has been used to monitor the solder joints. This approach has not previously been used as an effective tool in monitoring solder joints through life performance in vibration testing. The research regime proposed in this thesis was to monitor the health of solder joints through ultrasound images from beginning to failure, and to see how cracks initiate and propagate in them. The effect of the relative position and orientation on the reliability of the solder joints and the flip chips in the PCB was also studied. The data collected was analysed using MATLAB. The results have shown that three types of solder joints- healthy, partially fractured or fractured are formed near the time of complete failure of a flip chip. When about 70- 80% of the flip chips are either partially fractured or fractured a flip chip is expected to fail. The mean pixel intensity and area change in the acoustic image of a partially fractured or fully fractured joint tends to be higher compared to a healthy joint. Crack initiation in a joint occurs at around 35-40% cycling and propagates linearly till 80-85% cycling after which a joint fails. A statistical analysis done on the solder joints showed that the intensity distribution of healthy joints follow a simple Gaussian distribution while that of partially fractured or fractured joint can only be represented by using a mixture of Gaussians. The solder joints near the board edges are the least reliable in a vibration environment. However, solder joints with back to back connections are more reliable than the ones placed in one sided orientation. The most reliable flip chip orientation in a vibration environment is the back to back connection with no offset which was actually found to be the least reliable in the case of thermal cycling. Based on the analysis of the results, a few design guidelines for flip chip layout and orientations in a PCB has also been proposed in this work

Automatic Gradient Threshold Determination for Edge Detection Using a Statistical Model A Description of the Model and Comparison of Algorithms

In the enhancement/thresholding method of edge detection, the gradient values of pixels exceeding a certain threshold are designated as edge pixels. However, selecting a threshold has commonly been performed through ad hoc measures. This paper describes a method for automatically selecting a threshold using a 5-parameter model. The model is based on the weighted sum of two gamma density functions corresponding to edge and ncln-edge pixels. A variety of statistical and fitting methods for finding the model parameters were evaluated by comparing their computed thresholds to perceptual thresholds determined by subjects for 16 different images. The performance of the model was also analyzed under different noise levels. Index Terms: Automatic thresholding, edge detection, gradient, Sobel operator, statistical classification