A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal infinite impulse response zero crossing based edge detectors
CVGIP: Image Understanding
SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
Image Field Categorization and Edge/Corner Detection from Gradient Covariance
IEEE Transactions on Pattern Analysis and Machine Intelligence
A scene registration method based on a dynamical receptive field model of biological vision
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
Edge Detection with Embedded Confidence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
Logical/Linear Operators for Image Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Detection and Ridge Detection with Automatic Scale Selection
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
ISCV '95 Proceedings of the International Symposium on Computer Vision
Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
A model of contextual interactions and contour detection in primary visual cortex
Neural Networks - 2004 Special issue Vision and brain
Robustness of Shape Descriptors to Incomplete Contour Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour detection based on contextual influences
Image and Vision Computing
Extraction of salient contours from cluttered scenes
Pattern Recognition
A biologically motivated multiresolution approach to contour detection
EURASIP Journal on Applied Signal Processing
Multi-scale Improves Boundary Detection in Natural Images
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
Review article: Edge and line oriented contour detection: State of the art
Image and Vision Computing
Contour Detection and Hierarchical Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Image Processing Handbook, Sixth Edition
The Image Processing Handbook, Sixth Edition
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Bounded diffusion for multiscale edge detection using regularizedcubic B-spline fitting
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A geometric approach to edge detection
IEEE Transactions on Fuzzy Systems
Multiscale image segmentation by integrated edge and region detection
IEEE Transactions on Image Processing
Nonlinear operator for oriented texture
IEEE Transactions on Image Processing
Contour detection based on nonclassical receptive field inhibition
IEEE Transactions on Image Processing
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The broad region outside the classical receptive field (CRF) of a vision neuron, known as the non-classical receptive field (nCRF), exerts a robust modulatory effect on the responses to visual stimuli presented within the CRF, and plays an important role in visual information processing. One possible role for the nCRF is the extract object contours from disorderly background textures. In this study, a multi-scale integration based contour extraction model, inspired by the inhibitory and disinhibitory interactions between the CRF and the nCRF is presented. Unlike previous models, our model not only includes both the simple and complex cell mechanisms but also introduces pre-processing of the external information by the retinal ganglion cells at an early stage. The multi-scale representation of a physical scene acquired through such pre-processing was filtered through Gabor filters, and then inhibited or disinhibited at different spatial locations on different scales until a final response was obtained. Our results show that by introducing this kind of mechanism into the model, numbers of non-meaningful texture elements can be removed significantly, while at the same time, the object contours can be detected effectively. In addition to the superior contour detection performance in comparison to other contour detection models, our model provides a better understanding of the role of the nCRF and a novel approach for computer vision and pattern recognition.