Bernard Lamalle

Study of the imaging conditions and processing for the aspect control of specular surfaces

A vision system capable of imaging and detecting defects on reflective nonplanar surfaces in the production line at a high cadence is presented in this paper. Defects are typically dust located under the metallic layer of packaging products used in cosmetic industries. To realize this processing, structured lighting which reveals the defects in the image is proposed. Defects appear clearly in the images like a set of brilliant pixels in dark zones. The signature of the defect is then obtained. The size of this signature does not depend linearly on the size of the defect. It is a function of the observation angle. In order to realize a precise and robust process, the necessity of acquiring several images of the same defect is demonstrated. Because of the acquisition rate, it has been necessary to optimize image processing time by the means of an original laplacian filter and of high level techniques of programming. Results obtained using this detection system are finally presented.

Silicon retina for real-time pattern recognition

We present in this paper a programmable silicon retina designed for real-time pattern recognition. Its working principle is based on the comparison between an image projected on the retina by some opt9ical means and a reference binary image or mask memorized in the circuit. The result of the comparison is two signals corresponding to the sum of the currents produced by the pixels pertaining to the black and white zones of the reference binary image, this image when projected on the retina will produce a maximum white pixel current and a minimum black pixel current if it coincides perfectly with the reference binary image. If the projected image is shifted with respect to the reference binary image or if it is different then the black and white pixel currents will be different also. By measuring these two currents and by comparing them to expected values, a shift of the pattern or a difference between the observed and programmed pattern can be detected. Extensive computer simulations have been done in order to validate the working principle of the retina. Moreover, in order to verify the feasibility of the circuit in CMOS technology, we have fabricated a prototype non-programmable circuit in 1.2 micrometers standard CMOS technology. The measurements done on this circuit are quite encouraging and have been found to correspond to our expectations. Finally, the architecture of the programmable silicon retina, designed in a more recent 0.6 micrometers CMOS technology, is presented. This circuit is currently being fabricated.

A CMOS retina for Zernike moments estimation

Indeed, if we consider the real and imaginary parts of the Zernick polynomial of order p and repetition q as two images, then we can notice that there is a close relationship between the correlation value of two images and the expression of the real and imaginary parts of the Zernick moments of an image. Thus, the value of the Zernick moment of an image can be obtained by computing the correlation value between the image under analysis and two other images, one for the real part and another one for the imaginary part. The latter two images that depend on the order p and repetition q of the Zernick moment to compute are gray level images that need to be memorized in the retina. In order to reduce hardware implementation cost they are transformed into binary images or masks using a dithering algorithm. In this way only a 2-bit memory device is required per pixel to memorize the two masks (on bit per mask). Using the binary masks instead of the gray level images only gives an approximate value of the Zernick moments. However, we will show that the approximated values are still a good representation of the analyzed image (and thus can be used in a pattern recognition application). To do so, the exact and approximate values of the Zernick moments for values of p and q ranging from 0 to 30 have been computed and the images reconstructed from these values compared to the original one. The relative errors between the respective reconstructed images (exact and approximated Zernick moments) and the original image have been plotted against the orders of the Zernick moments used in the reconstruction. We have noticed that the evolutions of the error curves are quite similar.

Retina for pattern matching in standard 0.6-µm complementary metal oxide semiconductor technology

We present a silicon retina fabricated in standard CMOS 0.6-µm technology. The goal of the sensor is to determine whether or not two images are similar. An image known as the reference image is first used during a programming phase to classify the pixels into two zones that correspond to, respectively, the bright and dark pixels of the reference image. Next, an image is analyzed and the values of the pixels of each zone are summed to produce two signals denoted by Sn and Sb at the outputs of the circuit. If the image under analysis is different from the reference image, then the values of these two signals will also be different from those obtained with the reference image. Our circuit thus implements a pattern matching operation that allows us to determine the similarity between two images using the Sb/Sn plane. The architecture of the sensor is described, and both the simulation and the experimental results are given. Moreover, our pattern-matching operator is compared to the normalized correlation operator commonly used in pattern matching, and its performance is discussed. Finally, we present an example of the application of the sensor.

100-×100- pixel CMOS retina for real-time binary pattern matching

We present a 100-×100-pixel retina that can detect differences between an image under analysis and a reference image. The retina is realized in standard 0.6-μm CMOS technology with three layers of metal from Austria MicroSystems. Its total area is 34 mm 2 with a fill factor of about 37%.

Study and design of a programmable silicon retina for real-time pattern recognition

We present in this paper a prototype silicon retina that we have realized in standard CMOS technology. It is mainly composed of a photosensitive surface on which a metal layer representing a binary image is deposited. The partially masked photosensitive surface corresponds in fact to a photodiode which is directly connected to the output of the circuit. The readout signal is thus a current which is function of the luminous flux falling on the unmasked part of the photosensitive surface. It represents the correlation between an observed image and the reference image integrated on the sensor. The spatial sensitivity as well as the response of our retina as a function of a two-dimensional shifts between the reference image and an identical image projected on the sensor have been measured and found to correspond to our expectations. In order to improve the architecture of our retina for real time pattern recognition, we have done several computer simulations. The results of these simulations will be presented as well as the new architecture of our retina.

Online defects localization on mirrorlike surfaces

This paper deals with an on line defects detection system. This system is used for controlling surfaces reflecting as mirror. The originality of this work is the lighting used and the filter used to process the image. Developed lighting is a structured one. It is composed of a succession of luminous and dark stripes. Using this lighting, defects appear clearly on the images. Images obtained with this specific lighting are particular and very contrasted, for these reason an original filter, very easy to implement has been developed to process them. This filter looks like a morphological filter. Conception of the operator has been done in accordance to the knowledge of the shape of the defects to be detected. One of the important constraint of the system is the processing time, which must be very short to work on a standard PC at the flow rate of the industrial process.

Lighting study for an optimal defects detection by artificial vision

Lighting, which is an important side of quality control by artificial vision is often neglected. Scientists have to spend time and make several experiments before finding a good solution. We have chosen to study lighting of metallic objects according to the shape and the roughness of the object for an optimal defect detection. The first step of our study was to find a theoretical model of light scattering. To take into account reflection on smooth as well as rough surfaces, it is necessary to have a physical approach in the way of Beckmann and Spizzichino who based their model on electromagnetic wave theory. The general expression for surface radiance is a fairly complicated function of the angles of incidence and reflection, and the surface roughness parameters. Radiance diagrams of this model give the light intensity reflected by an elementary surface in all the directions. Thanks to this model, we are able to optimize the size and position of the source according to the shape and the roughness of the object and the type of defects to detect. In the field of artificial vision, the conceivable applications are numerous: for instance one can quote defect detection (scratches, knocks...) or dimensional control of object (swell or undulation measurement...).

Hardware Computation of Moment Functions in a Silicon Retina using Binary Patterns

We present in this paper a method for implementing moment functions in a CMOS retina for shape recognition applications. The method is based on the use of binary patterns and it allows the computation of different moment functions such geometric and Zernike moments of any orders by an adequate choice of the binary patterns. The advantages of the method over other methods described in the literature is that it is particularly suitable for the design of a programmable retina circuit where moment functions of different orders are obtained by simply loading the correct binary patterns into the memory devices implemented on the circuit. The moment values computed by the method are approximate values, but we have verified that in spite of the error the approximate values are significant enough to be applied to classical shape localization and shape representation and description applications.

CMOS image sensor for spatiotemporal image acquisition

We present a 64-×64-pixel CMOS image sensor chip that can acquire a 16-gray-level image containing both spatial and temporal information of the moving luminous object under observation. The image can next be processed using any image processing software in order to determine the speed, trajectory, and direction of motion of the moving object. The architecture of the sensor and an example of its application to the determination of the speed of a moving laser spot are described.