The role of features in structuring visual images
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Updated: Sep 9, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Published on: November 2, 2012
1Istituto di Neurofisiologia del CNR, Pisa, Italy.
Abstract:
Edges and lines carry much information about images and many models have been developed to explain how the human visual system may process them. One recent approach is the local energy model of Morrone and Burr. This model detects and locates both lines and edges simultaneously, by taking the Pythagorean sum of the output of pairs of matched filters (even- and odd-symmetric operators) to produce the all-positive local energy function. Maxima of this function signal the presence of all image features that are then classified as lines or edges (or both) and as positive or negative, depending on the strength of response of the even- and odd-symmetric operators. If the feature is an edge, it carries with it a brightness description that extends over space to the next edge. The model successfully explains many visual illusions, such as the Craik-O'Brien, Mach bands and a modified version of the Chevreul. Features can structure the visual image, often creating appearances quite contrary to the physical luminance distributions. In some examples the features dictate totally the image structure, 'capturing' all other information; in others the features are seen in transparence together with an alternate image. All cases can be predicted from the rules for combination of local energy at different scales.
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