The Nonlinear Memristive Grid

Nonlinear resistive grids have been proposed previously for image smoothing that preserves discontinuities. The recent development of nonlinear memristors using nanotechnology has opened the possibility for expanding the capabilities of such circuit networks by replacing the nonlinear resistors with memristors. We demonstrate here that replacing the connections between nodes in a nonlinear resistive grid with memristors yields a network that performs a similar discontinuity-preserving image smoothing, but with significant functional advantages. In particular, edges extracted from the outputs of the nonlinear memristive grid more closely match the results of human segmentations.

[1]  L. Chua.  Memristor-The missing circuit element , 1971 .

[2]  Leon O. Chua,et al.  Resistive grid image filtering: input/output analysis via the CNN framework , 1992 .

[3]  Jitendra Malik,et al.  Learning to Detect Natural Image Boundaries Using Brightness and Texture , 2002, NIPS.

[4]  D. Stewart,et al.  The missing memristor found , 2008, Nature.

[5]  John L. Wyatt,et al.  CMOS resistive fuses for image smoothing and segmentation , 1992 .

[6]  Andrew Blake,et al.  Visual Reconstruction , 1987, Deep Learning for EEG-Based Brain–Computer Interfaces.

[7]  J. G. Harris,et al.  Discarding outliers using a nonlinear resistive network , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

[8]  Jitendra Malik,et al.  A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[9]  C Koch,et al.  A two-dimensional analog VLSI circuit for detecting discontinuities in early vision. , 1990, Science.

[10]  Demetri Terzopoulos,et al.  Regularization of Inverse Visual Problems Involving Discontinuities , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Christof Koch,et al.  Vision Chips: Implementing Vision Algorithms with Analog VLSI Circuits , 1994 .

[12]  W. Millar.  CXVI. Some general theorems for non-linear systems possessing resistance , 1951 .

[13]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Niklas Nordström,et al.  Biased anisotropic diffusion: a unified regularization and diffusion approach to edge detection , 1990, Image Vis. Comput..

[15]  T. Poggio,et al.  III-Posed problems early vision: from computational theory to analogue networks , 1985, Proceedings of the Royal Society of London. Series B. Biological Sciences.