Title :
Figure-ground separation by a neural dynamical system
Author :
Zhang, Jun ; Jianhua Lin
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Wisconsin Univ., Milwaukee, WI, USA
Abstract :
This paper describes a neural network inspired dynamical system approach to a perceptual grouping problem-figure-ground separation. In this approach, a non-linear differential equation is defined at each pixel site and coupled with those at its neighbours. The steady state solution would determine whether a pixel is part of a salient structure or background/noise. The neighbourhood couplings are used to achieve spatial interactions that are essential to perceptual grouping, such as excitation and inhibition. Experimental results on the grouping of dots in synthetic and real-world images demonstrate the efficacy of the proposed approach
Keywords :
image recognition; neural nets; nonlinear differential equations; object recognition; visual perception; dot grouping; excitation; figure-ground separation; inhibition; neighbourhood couplings; neural dynamical system; neural network inspired dynamical system; nonlinear differential equation; perceptual grouping; perceptual grouping problem; real-world images; spatial interactions; steady state solution; synthetic images; Background noise; Computer vision; Feature extraction; Humans; Image edge detection; Image processing; Image segmentation; Machine vision; Neural networks; Nonlinear equations;
Conference_Titel :
Image Processing, 1995. Proceedings., International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-8186-7310-9
DOI :
10.1109/ICIP.1995.537554