A two-dimensional analog VLSI circuit for detecting discontinuities in early vision

Stochastic artificial retinas: algorithm, optoelectronic circuits, and implementation

An analogy can be established between image processing and statistical mechanics. Many early- and intermediate-vision tasks such as restoration, image segmentation, and motion detection can be formulated as optimization problems that consist in finding the ground states of an energy function. This approach yields excellent results, but, once it is implemented in conventional sequential workstations, the computational loads are too extensive for practical purposes, and even fast suboptimal optimization approaches are not sufficient. We elaborate on dedicated massively-parallel integrated circuits, called stochastic artificial retinas, that minimize the energy function at a video rate. We consider several components of these artificial retinas: stochastic algorithms for restoration tasks in the presence of discontinuities, dedicated optoelectronic hardware to implement thermal motion by photodetection of speckles, and hybrid architectures that combine optoelectronic, asynchronous-analog, and clocked-digital circuits.

A Floating-Gate MOS Implementation of Resistive Fuse

Resistive fuses are key elements in weak string filters, which smooth out noise while detecting step edges inherent in original data. A resistive fuse is implemented by two pairs of floating-gate metal oxide semiconductor (MOS) transistors in a chip by a standard double poly complementary MOS process.