A sorting image sensor: an example of massively parallel intensity-to-time processing for low-latency computational sensors

The need for low-latency vision systems is growing: high speed visual servoing and vision-based 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 low-latency 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