Rockwell International Corporation

Bimal P Mathur

H Taichi Wang

Shih-Chii Liu

David Lawrence Standley

Richard S Haendel

Christof Koch

Craig Charles Reinhart

John G Harris

A nonlinear resistive network, which includes switches in the data paths, is provided for identifying, isolating, and/or rejecting outliers in a sensor image. During normal operation, images are received with all the switches in a closed (conducting) state. If the data at a given pixel is different from its immediate neighbors by a predetermined threshold voltage, its switch is opened. A readout of the state of all the switches in the network yields a map of points sources, and a readout of the network voltages yields a noise-free image. Because the threshold voltage can be controlled externally, various strategies may be implemented for identification of the outliers in a computer vision system.

Nonlinear resistive network for isolating outliers in sensor images

An analog VLSI circuit having a network of resistive elements and switches is provided for discriminating between an object and the background in a sensor image of a scene. A sensor system captures two-dimensional visual images and identifies edges of objects. The output of the imaging system is mapped onto the switched resistive grid. The presence of object edges causes switches to open at corresponding grid points in the resistive network. The periphery of the grid is connected to a first voltage, while a central point of the grid is connected to a second voltage. An edge map contour of open switches surrounding the central point causes the voltage at every point within the contour to rise to the second voltage, while every grid point outside the contour settles to the first voltage. Thus, the object enclosed by the edge map contour is labeled or tagged with the second voltage and the surrounding background is characterized by the first voltage. The object-background segregation occurs in parallel, independent of the complexity or arc length of the edge map contour. Nonlinear resistive elements, such as saturating resistive circuits, may be used to limit current flow through gaps or breaks in the contour. This prevents full voltage equalization and allows object-background discrimination for discontinuous contours based on a selected voltage threshold.

Object-background discrimination using analog VLSI circuit

A vehicular traffic monitoring system incorporates an array of photosensors and a nonlinear resistive network for identifying, locating, and processing outliers in sensor images of a highway or intersection. The camera system can be mounted on a pole or overpass to provide an image of the roadway or intersection. Areas of the outlier network ('video loops') are designated to correspond to selected areas of the roadway. Images are received by the outlier detection network with all data path switches closed between sensor elements and their corresponding network nodes. The system detects the presence of objects in the image by comparing the brightness or intensity of each pixel with that of the background. If the intensity of a pixel is significantly different from the background level, the data path switch corresponding to that pixel is opened. A readout of the state of all the switches in the network yields a map of outlier points for each video frame. The outlier map is connected to a data processing system to identify and locate outlier points in the image. The detection of a threshold number of outliers in a video loop indicates the presence of a vehicle at the corresponding area of the roadway. The processor, having a greatly reduced computational load without extensive image processing, simply measures and transmits traffic data such as the number and speed of vehicles passing through the video loops.

Vehicular traffic monitoring system

A low cost, real time vehicle lane position detection system is provided for determining and maintaining the position of the vehicle on a highway. The system comprises an image sensor mounted on the front of an automotive vehicle and an integrated processor for performing real-time lane mark detection. The sensor/processor system identifies highway lane marks on the detector image plane by using a nonlinear resistive network for detecting outliers. A line detection algorithm, such as the Hough transform, is used to determine the lane marks from the outliers on the image plane. Because the expected lane position can be determined in advance, an added degree of signal-to-noise discrimination is achieved by providing feedback to the processor for outlier detection. The position of the vehicle in the lane is determined and tracked from the position of the detected lane marks on the image plane given the sensor position and optical geometry.

Vehicle lane position detection system

A system of active emitters and sensors is provided for measuring distance and communicating between vehicles on an automated highway. The preferred system utilizes a pair of spaced apart sensors at the front of each vehicle for stereo depth perception, two temporally modulated emitters on the rear of each vehicle for redundancy and inter-vehicle communication, and temporally modulated emitters positioned at intervals along the highway for communication from the highway to the vehicles. The emitters may transmit radiation at a wavelength, such as 1 .mu.m IR, for example, that can be detected by low cost detectors. The emitters are modulated temporally to transmit a binary code, resulting in signal-to-noise improvement and increased clutter rejection and operational range. Each sensor may include an array of IR detectors and associated readout circuitry, an imaging lens, a lens array for improving detector fill factor, a filter and polarizer to reject clutter and reduce noise, and a cylindrical lens to provide a good vertical field of view. Detector charge integration is controlled by the binary code of the emitters and depends on the code length and local background illumination. The sensors are connected to a computer processor for processing data received from the emitters and computing distance between vehicles.

Inter-vehicle distance measuring system

An electronic image processing system uses data provided by one or more sensors to perform cooperative computations and improve image recognition performance. A smoothing resistive network, which may comprise an integrated circuit chip, has switching elements connected to each node. The system uses a first sensory output comprising primitives, such as discontinuities or object boundaries, detected by at least a first sensor to define a region for smoothing of a second sensory output comprising at least a second, distinct output of the first sensor or a distinct output of at least a second sensor. A bit pattern for controlling the switches is generated from the detected image discontinuities in the first sensory output. The second sensory output is applied to the resistive network for data smoothing. The switches turned off by the data from the first sensory output define regional boundaries for smoothing of the data provided by the second sensory output. Smoothing operations based on this sensor fusion can proceed without spreading object characteristics beyond the object boundaries.

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Thousand Oaks, CA, United States of America

Bimal P Mathur