Robotics Institute
School of Computer Science, Carnegie Mellon University
A Sorting Image Sensor: An Example of Massively
Parallel Intensity-to-Time Processing for Low-Latency Computational
Sensors
Vladimir Brajovic
January 1996
The need for low-latency vision systems is growing: high speed visual
servoing and visionbased human computer interface. In this paper we
present a new intensity-to-time processing paradigm suitable for
low-latency massively parallel global computation over fine-grained
data such as images. As an example of a lowlatency global computation,
we have developed a VLSI sorting computational sensor - a sensor
which sorts all pixels of an input image by their intensities, as
the image is being sensed. The first sorting sensor prototype is a
21 by 26 array of cells. It detects an image focused thereon and
computes the image of indices as well as the image's cumulative
histogram, before the intensity data are readout. The image of indices
never saturates and has uniform histogram. Under user's control, the
chip can perform other operations including simple segmentation and
labeling.
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