Denis Poussart

A computer-vision technique for the acquisition and processing of 3-D profiles of dental imprints: an application in orthodontics

The authors present a computer vision technique for the acquisition and processing of 3-D images of the profile of wax dental imprints in the automation of diagnosis in orthodontics. The acquisition of the 3-D images is based on the absorption of light by a dispersive medium and uses standard CCD (charge coupled device) cameras. The profiles of both sides of the imprint are acquired simultaneously. The 3-D image of each side of the imprint is segmented by nonlinear filtering of the 3-D data, and the interstices between the teeth are detected. Two operators are presented: one for the detection of the interstices between the teeth for incisors, canines, and premolars, and one for those between molars. A method for deciding the optimal neighborhood of application of each operator is also presented. Experimental results show that the two operators are very effective at detecting the interstices.

3-D Sensing for industrial computer vision

Computer vision is becoming an important issue in many industrial applications such as automatic inspection of manufactured parts, robotic manipulations, autonomous vehicle guidance, and automatic assembly. Since these applications are performed in a three-dimensional world, it is imperative to gather reliable information on the 3-D structure of the scene. Range-finder cameras are usually used to collect 3-D data. This chapter presents a review of various range-finding techniques. Early designs and more recent developments are discussed along with a critical assessment of their performances. Purely optical techniques are not covered.

Rapid measurement of system kinetics—An instrument for real-time transfer function analysis

The characterization of input-output relationships in reponse to small perturbations is a basic approach to the experimental study of a variety of systems. These exist numerous instances where, in addition to convenience, messurements should be performed in a minimum time. This papeg describes a method whereby a pseudo-random binary signal, properly filtered and synchronised, is used in conjunction with fast digital Fourier transform techniques to yield rapid transfer function estimates. Its implementation results in a novel instrument which is well adapted to real-time on-line applications. Evaluation in the course of studies on electrical characteristics of nerve membrane have confirmed its rather unique combination of speed, dynamic range, accuracy, and flexibility of operation.

Estimating the 3D rigid transformation between two range views of a complex object

Presents a method to compute the inter-frame transformation between two range image views of complex multi-part objects. No exact feature matching is attempted and no initial approximate transformation is provided. The method is naturally decomposed into two stages of initial estimation and final refinement of the transformation. A hierarchical triangulation-based surface representation provides an efficient way to select the control points at which the alignment of the two surfaces is to be evaluated. This representation also permits the selection of a manageable number of initial transformations among which at least one is to be in the parametric neighborhood of the actual transformation. Experimental results show that the computed transformation between two views of a complex multi-part object may provide angles of rotation within a fraction of a degree of the actual ones.<<ETX>>

Scene reconstruction and description: geometric primitive extraction from multiple viewed scattered data

Robust extraction of surface parameters from multiple view scattered and noisy 3-D measurements is a delicate task. It is shown that a stable local surface description can be extracted on sections where measurement constraints are redundant with respect to a polynomial model. A segmentation approach is developed to identify these sections. The approach is based on a measurement error model which takes into account the sensors viewpoint. An application of the approach to the extraction of straight line sections from single scan 3-D surface profiles is presented.<<ETX>>

High resolution smart image sensor with integrated parallel analog processing for multiresolution edge extraction

Abstract This paper presents a vision sensor which generates a multiresolution edge description using parallel analog processing support. Its multimodule architecture is based on a Multi-port Access of photo-Receptor (MAR) hexagonal sensor coupled to an external but powerful analog processing unit and a microcoded digital interface. The system supports image scanning and edge tracking. Satellite analog processing allows extensive computation using VLSI technology, leaving all the sensor area available for photo-transduction and communication pathways. It is thus possible to design a sensor with up to 500 × 500 pixels on a single CMOS chip using 1.2 μm technology. The goal of the approach described here is to exploit an imbedded edge tracing algorithm in order to generate a scene description as a list of connected edge segments. Experimental results are presented for the current prototype which implements 256×256 pixels with corresponding multiresolution edge maps.

Motion vision sensor architecture with asynchronous self-signaling pixels

A custom CMOS imager with integrated motion computation is described. The architecture is based on correlating in time moving edges. Edges are located in time by a custom sensor; and correlated in a coprocessing module. The sensor architecture is centered around a compact pixel with analog signal processing and digital self-signaling capabilities. The sensor pixels detect moving edges in the image and communicate their position using an address-event protocol associated to temporal stamps. The coprocessing module correlates the edges and computes the velocity vector map. The motion sensor could be used in applications such as self-guided vehicles, mobile robotics and smart surveillance systems. The article details the motion sensor architecture, the simulated performance, the VLSI implementation and some preliminary results on fabricated prototypes.

A Focal Plane Architecture for Motion Computation

A new focal plane architecture for motion computation is presented. The design is based on the Smart Sensor paradigm: combining transduction and early processing at sensor level. The sensor computes focal plane motion and direction in a subsampled space, with programmable spatio-temporal bandwidth. The architecture is designed around an array of neuromorphic analog processing cells with local photo-transduction, computation of temporal variations in the image and correlation between neighbor pixels. The inherent process of serial read-out is used for further integration of low-level processing and reduction of complexity of each pixel. An external dedicated digital processor controls the system, interprets, and integrates the information from sets of four processing pixels in order to create a motion-based medium-level description of the image. The approach developed for VLSI implementation offers an excellent combination of small pixel area and a computationally efficient method for image motion measurement. The architecture is being implemented in a standard 1.5 ?m CMOS process.

Membrane Ionic Currents, Current Noise, and Admittance in Isolated Cockroach Axons

The application of fluctuation analysis to conduction processes in excitable membranes has developed rapidly since the early work of Derksen and Verveen (1966) on the node of Ranvier. First recordings of membrane current noise were made on the giant axon of the lobster (Poussart, 1969, 1971) and showed that the spontaneous noise consisted mainly of a 1/f component with an intensity related to the driving force for potassium ions. A second noise component with the apparent form of a relaxation process, 1/[1 + (f/f c )2], was later observed in both squid axons (Fishman, 1973; Conti et al., 1975; Fishman et al., 1975a) and frog nodes of Ranvier (Siebenga et al., 1973). Since then, numerous experiments have been done on these last two preparations and noise spectra arising from the transitions between “open” and “closed” states of sodium and potassium channels have been characterized. The relationship between the frequency characteristics of this noise and the observed or computed kinetics of the sodium and potassium conductances is, however, still controversial. In large-area noise measurements of squid axon, several technical problems such as low input impedance, potassium accumulation in the periaxonal space, and electrode polarization provide some impediments to a good quantitative analysis of ionic channel noise. In nodes of Ranvier, the situation is better but extrinsic noise is quite high and potassium also accumulates externally during long-lasting depolarizations.

Mixed-signal VLSI Architecture for Real-Time Computer Vision

This paper presents the architecture of a computer vision system targeted for real-time robot vision and pattern recognition applications. The proposed mixed-signal very large scale integration (VLSI) architecture integrates photo-transduction with low- and medium-level processing such as multi-resolution edge extraction, scale-space integration, edge tracking, dominant point extraction, and database generation. Its high performance stems from a custom CMOS smart image sensor providing parallel access to illuminance data and a set of parallel analog filters performing multi-resolution edge extraction. We have also developed a digital controller which manages data flow between the processing modules of the system and which constructs a database of the observed scene under the supervision of a digital signal processor (DSP) unit. This database describes relevant object contours as a linked list of linear segments and circular arcs with precomputed local and global properties. Such a token description of the scene is suitable for robot vision and pattern recognition applications, since it significantly compresses the amount of data to be processed by further high-level algorithms. Experimental results obtained with the current prototype of the system are very promising, with the complete process, from image acquisition to scene database creation, performed in less than a second.