Benaissa Bellach

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.

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%.

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.

Correlation retina in standard 0.6μm: application in positioning system

We have designed and fabricated a programmable retina that is capable of recognizing patterns stored in memory in real-time. Each of the pixels of the retina is composed of a photodiode and an electronic device used during the programming phase to digitize the image of the pattern to recognize into a binary image stored in latches. The array of pixels is thus partitioned into two complementary disjoint sub-sets with all the photodiodes of the same sub-set connected together in order to obtain the sum total of the currents. During the analysis phase, an optical correlation between the projected image and the reference binary image memorized in the circuit is done. The result is read-out as two voltages representing the following two currents: a “white” current proportional to the luminous flux falling on the photodiodes pertaining to the “white” part of the binary reference image and a “black” current corresponding to the black part. By comparing these two voltages to expected values, a shift of the pattern or a difference between the observed and programmed pattern can be detected. The retina has been fabricated in standard 0.6μm CMOS technology with three layers of metal from Austria Micro Systems. It consists of a 100×100 pixels image sensor. We present here an application of this sensor for industrial positioning system.

CMOS image sensor dedicated to speed determination of fast moving luminous objects

We present a CMOS image sensor for speed determination of fast moving luminous objects. Our circuit furnishes a 16-gray level image that contains both spatial and temporal information on the fast moving object under observation. The spatial information is given by the coordinates of the illuminated pixels and the temporal information is coded in the gray level of the pixels. By applying simple image processing algorithms to the image, the trajectory, direction of motion and speed of the moving object can be determined. The circuit is designed and fabricated in standard CMOS 0.6μm process from Austria MicroSystems (AMS). The core of the circuit is an array of 64 × 64 pixels based on an original Digital Pixel Sensor (DPS) architecture. Each pixel is composed of a photodiode as the light sensing element, a comparator, a pulse generator and a 4-bit static memory for storing the gray value of the pixel. The working principle of the circuit, its design and some quantitative experimental results are presented in the paper.

CMOS image sensor design for speed determination of fast moving luminous objects

We present a CMOS image sensor for speed determination of fast moving luminous objects. Our circuit furnishes a 16-gray level image that contains both spatial and temporal information on the fast moving object under observation. The spatial information is given by the coordinates of the illuminated pixels and the temporal information is coded in the gray level of the pixels. By applying simple image processing algorithms to the image, trajectory, direction of motion and speed of the moving object can be determined. The circuit is designed and fabricated in standard CMOS 0.6 μm process from Austria MicroSystems (AMS). The core of the circuit is an array of 64×64 pixels based on an original Digital Pixel Sensor (DPS) architecture. Each pixel is composed of a photodiode as the light sensing element, a comparator, a pulse generator and a 4-bit static memory for storing the gray value of the pixel. The working principle of the circuit, its design and some quantitative experimental results are presented in the paper.

CMOS image sensor for the analysis of fast-moving luminous objects

We present an image sensor dedicated to the analysis of fast moving luminous objects. The circuit is fabricated in standard 0.6 μm CMOS technology with an image sensing array of 64 x 64 pixels. Its working principle is as follows: An electronic unit integrated at the pixel level measures the elapsed time since the beginning of the acquisition till the passage of the luminous object in front of the pixel under consideration. This value that corresponds to a number of clock cycles is stored in a 4-bit memory at the pixel level and translated into a gray level, the brighter ones corresponding to the shortest time. The result is a 16-gray level image that represents the trajectory and direction of motion of the object. Knowing the frequency of the clock, the distance between the pixels and the difference in gray levels of the pixels, the speed of the moving object can be determined. Alternatively, the 16-gray level image can be considered as a superposition of 16 one gray level images that represent the 16 positions of the moving object at 16 different time instances in the course of its displacement. The frequency of the clock can be as high as 20 MHz for the analysis of very high speed phenomena. The working principle and the architecture of the image sensor will be described in details in this paper. Moreover, the results of the tests carried out on the circuit, namely the analysis of the movement of the spot on an oscilloscope screen, will also be reported and the potential applications of the image sensor discussed.