Patrick Gorria

Vision system for defect imaging, detection, and characterization on a specular surface of a 3D object

Abstract A vision system capable of imaging, detecting, and characterizing defects onto highly reflective, non-plane surfaces, is presented in this paper. Defects are typically dust, and hair located under the metallic layer of packaging products used in cosmetic industries. The vision system comprises an innovative lighting solution to reveal defects onto highly reflective non-plane surfaces. Several image acquisitions are performed to build a synthetic image, where defects clearly appear white on a mid-gray background. Our lighting system allows imaging defects on various-shaped objects. The vision system measures the defect size to make a decision on the product rejection. The authors assess system performance by conducting series of tests.

Simulation of specular surface imaging based on computer graphics: application on a vision inspection system

This work aims at detecting surface defects on reflecting industrial parts. A machine vision system, performing the detection of geometric aspect surface defects, is completely described. The revealing of defects is realized by a particular lighting device. It has been carefully designed to ensure the imaging of defects. The lighting system simplifies a lot the image processing for defect segmentation and so a real-time inspection of reflective products is possible. To bring help in the conception of imaging conditions, a complete simulation is proposed. The simulation, based on computer graphics, enables the rendering of realistic images. Simulation provides here a very efficient way to perform tests compared to the numerous attempts of manual experiments.

Dynamic lighting system for specular surface inspection

Specular surfaces inspection is a problem met frequently within the automatic control of metallic products. A tried technique to reveal the aspect defects is the imaging of the reflection of a structured lighting as Dark Field Illumination through the surface. In order to inspect the whole surface, an element of the lighting structure has to scan every part of the surface. In the case of important surface curvature gradients, entire scanning is not ensured if the object is moving in front of the static lighting. To overcome this limitation, an inverse process is proposed: the lighting structure is dynamic while the object is static. The scanning of the surface by the various lighting configurations enables the aspect control. A modeling of the surface to be inspected and defects to be detected is made. Inverse ray tracing is used to analyze the reflection of the lighting through the surface. This modeling enables to ensure the revealing of defects by respecting the chosen criteria of detection. A relation binding the physical size of defects and its size on the image is established. A metrological approach of the problem is then performed.

3D characterization of hot metallic shells during industrial forging

During industrial forging of hot metallic shells, it is necessary to regularly measure the dimensions of the parts, especially the inner and outer diameters and the thickness of the walls. A forging sequence lasts 2 h or more during which the diameter of the shell is regularly measured in order to decide when to stop the forging process. For better working conditions, for the safety of the blacksmiths, and for a faster and more accurate measurement, we have developed a novel system based on two commercially available time of flight laser scanners for the measurement of the diameters of hot cylindrical metallic shells during the forging process. The advantages of using laser scanners are that they can be placed very far from the hot shell, more than 15 m, while at the same time giving an accurate point cloud from which three-dimensional views of the shell can be reconstructed and diameter measurements done. Moreover, more accurate measurement is achieved in less time with the laser system than with the conventional method using a large ruler. The system has been successfully used to measure the diameters of hot cylindrical metallic shells.

An edge detection ASIC for real time defect detection

The design of a low cost real-time image processing microsystem for detecting defects in manufacturing products is presented. The analysis method is based on an edge detection algorithm (differential operators) to select the information related to the structure of the objects present in the image. The edge calculation function is integrated in a standard cell circuit, using a CMOS 1.5- mu m process. The ASIC is implemented and tested in an image processing microsystem with a CCD camera. Results show an improvement of performance in comparison with the first prototypes, allowing the use of this system in an industrial environment for the real-time detection of defects.<<ETX>>

Patterned wafer segmentation

This paper is an extension of our previous work on the image segmentation of electronic structures on patterned wafers to improve the defect detection process on optical inspection tools. Die-to-die wafer inspection is based upon the comparison of the same area on two neighborhood dies. The dissimilarities between the images are a result of defects in this area of one of the die. The noise level can vary from one structure to the other, within the same image. Therefore, segmentation is needed to create a mask and apply an optimal threshold in each region. Contrast variation on the texture can affect the response of the parameters used for the segmentation. This paper shows a method to anticipate these variations with a limited number on training samples, and modify the classifier accordingly to improve the segmentation results.

Parallel processor for image segmentation

We present the architecture of a parallel processor which is suitable for image segmentation. The classification of each pixel is completed using a geometric classification method by stress polytope training, which ensures a high decision speed (100 ns per pixels) and good performances. The decision operator has been integrated in the form of a full custom circuit developed in CMOS 1.2 /spl mu/m, and the area of silicon obtained is less than 30 mm/sup 2/.<<ETX>>

Content-based segmentation of patterned wafer for automatic threshold determination

This paper introduces a segmentation algorithm suitable for semiconductor wafer images generated by optical inspection tools. The primary application of this work is content-based region segmentation for automatic threshold selection during recipe generation in die-to-die wafer inspection. Structures associated with different functional areas lead to different levels of noise in the difference image during the defect detection process. The ability to automatically create a mask to separate the different structures and materials is necessary to determine local thresholds for each area and thus to improve the signal-to-noise ratio. A supervised segmentation based on the discrete wavelet transform is used to segment a whole die to create a mask. During the inspection, the mask is applied on the difference image, and the threshold is automatically set as a function of the noise within the region and the thresholding coefficient specific to that region. Preliminary segmentation results are very promising. The use of the segmented region in content-based threshold defect detection improves the number of defects detected, and reduces the number of false detections. This paper will show the performance of the segmentation method on optical microscope wafer images, and the subsequent improvement of the defect detection process.

Active Lighting Applied to Shape from Polarization

We present a new way of solving the ambiguity that appears in the shape from polarization method. This ambiguity, concerning the normals orientation of the surface, was previously solved thanks to a propagation algorithm. In this paper, the ambiguity is solved thanks to a special active lighting. This method is less time computing and is more robust to noise acquisition. We first demonstrate how to compute the right normals on the whole surface. Then, we show an application on the 3D reconstruction of a specular metallic object made by stamping and polishing.

Merging system for multiscale edge detection

We present a multiscale edge detection algorithm whose aim is to detect edges whatever their slope. Our work is based on a gener- alization of the Canny-Deriche filter, characterized by a more realistic edge than the traditional step shape edge. The filter impulse response is used to generate a multiscale edge detection scheme. For the merging of the edge information, we use a geometrical classifier developed in our laboratory. The segmentation system thus set up, after the training phase, does not require any adjustment or depend on any parameter. The main original property of this algorithm is that it leads to a binary edge image without any threshold setting. The quality of the results is inferior to that for classical multiscale merging approaches; nevertheless, this system, studied for real-time functioning, presents satisfactory per- formance for well-contrasted images and excellent performance for noisy