National Science Foundation
Enhancing Robot Vision
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Vision sensor for future intelligent systems.

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State: Pennsylvania

Most present and future vision applications including automotive, biometric, security and mobile computing applications operate in unconstrained environments and have to cope with unknown and widely varying illumination conditions. Even when illumination conditions do not saturate an image sensor, the vision system has to account for object appearance variations caused by illumination. By eliminating illumination-induced variations from the raw optical images the proposed sensor will eradicate the vision system’s vulnerability to illumination variations and signal loss due to high dynamic range.

This adaptive CMOS image sensor will estimate and largely eliminate illumination variations in sensed optical images, thus reporting electronic images that are indicative of the reflectance of the viewed scene. The core innovation is in a signal processing technique for estimating the illumination field from sensed images. The technique efficiently implements as a dense, on-chip, massively parallel analog processor, distributed among the photo-detectors to produce a reflectance sensitive image sensor.

Image sensors are rapidly finding their way into people’s cars, cell-phones, personal digital assistants, medical and diagnostic equipment, automated drug discovery, cutting edge security, surveillance and biometric systems. To fully realize the potential of electronic imaging in society, the image sensors will need to adapt and provide useful images most of the time, even under the harshest of illumination conditions.

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