A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Signal Processing for Computer Vision
Signal Processing for Computer Vision
Pedestrian Detection Using Wavelet Templates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Image Statistics and Anisotropic Diffusion
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Evaluation of global thresholding techniques in non-contextual edge detection
Pattern Recognition Letters
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Bayesian tree-structured image modeling using wavelet-domain hidden Markov models
IEEE Transactions on Image Processing
A steerable complex wavelet construction and its application to image denoising
IEEE Transactions on Image Processing
Edge detection of color images using directional operators
IEEE Transactions on Circuits and Systems for Video Technology
A survey of architecture and function of the primary visual cortex (V1)
EURASIP Journal on Applied Signal Processing
Pattern Recognition Letters
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We present a novel approach for automatically building image-specific extrapolative spatial models of non-boundary local energy that can be used to perform local statistical tests to detect perceptual boundaries. The non-boundary model consists of statistics of local energy that are spatially extrapolated by a non-boundary confidence map and a scale-adaptive normalised filtering algorithm. We exploit the flexibility of steerable filters to both extract oriented local energy and to provide local statistics of the energy distribution in the orientation-domain to compute the non-boundary confidence map. Finally, we apply our local thresholding technique separately to the three channels of colour images and adopt a max operator to combine the results. We provide a qualitative and quantitative comparison on real images from a hand-segmented natural image database against the best combination of the most widely cited colour edge detectors and automatic global thresholding methods.