The stability and control of discrete processes
The stability and control of discrete processes
A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Trace Inference, Curvature Consistency, and Curve Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Grouping contours by iterated pairing network
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Nonlinear Image Filtering with Edge and Corner Enhancement
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks - Special issue: automatic target recognition
Inferring global perceptual contours from local features
International Journal of Computer Vision - Special issue on computer vision research at the University of Southern California
Image segmentation based on oscillatory correlation
Neural Computation
SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
The Dynamics of Nonlinear Relaxation Labeling Processes
Journal of Mathematical Imaging and Vision
A neural model of contour integration in the primary visual cortex
Neural Computation
Perceptual organization of occluding contours of opaque surfaces
Computer Vision and Image Understanding - Special issue on perceptual organization in computer vision
A Comparison of Measures for Detecting Natural Shapes in Cluttered Backgrounds
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
Deformable Kernels for Early Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Perceptual Organization of Texture Flow: A Contextual Inference Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spike-Timing-Dependent Hebbian Plasticity as Temporal Difference Learning
Neural Computation
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The paper describes a new adaptive neural network for edge-based pattern extraction problems. In the model, each neuron represents an edge with continuous state variables describing its location and orientation. The post-synaptic distribution is dependent on the state variables. Each neuron adjusts its state to increase its membrane potential, which results in highly adaptive dynamics of the synaptic weight distribution. The network allocates multiple neurons with different orientation modes for each edge. The strategy allows accurate modeling of multi-modal distributions at key-points such as corners and junctions. As a result, the network delineates edges at sub-pixel accuracy while preserving key-points. It is also capable of processing a sequence of images and following moving objects. The network is extended for contour integration and key-point detection tasks. The paper presents experiments conducted on both synthetic and non-synthetic data to demonstrate the effectiveness of the technique.