Abstract
The detection of discontinuities in motion, intensity, color, and depth is a well studied but difficult problem in computer vision. We discuss our “resistive fuse” circuit—the first hardware circuit that explicitly implements either analog or binary line processes in a controlled fashion. We have successfully designed and tested an analog CMOS VLSI circuit that contains a 1-D resistive network of fuses implementing piece-wise smooth surface interpolation. The segmentation ability of this network is demonstrated for a noisy step-edge input.
We derive the specific current-voltage relationship of the resistive fuse from a number of computational considerations, closely related to the early vision algorithms of Koch, Marroquin and Yuille (1986) and Blake and Zisserman (1987). We discuss the circuit implementation and the performance of the chip. In the last section, we show that a model of our resistive network—in which the resistive fuses have no internal dynamics—has an associated Lyapunov function, the co-content. The network will thus converge, without oscillations, to a stable solution, even in the presence of arbitrary parasitic capacitances throughout the network.
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Harris, J., Koch, C., Luo, J., Wyatt, J. (1989). Resistive Fuses: Analog Hardware for Detecting Discontinuities in Early Vision. In: Mead, C., Ismail, M. (eds) Analog VLSI Implementation of Neural Systems. The Kluwer International Series in Engineering and Computer Science, vol 80. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1639-8_2
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DOI: https://doi.org/10.1007/978-1-4613-1639-8_2
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