A scale-vector approach for edge detection
Pattern Recognition Letters
Using models of feature perception in distortion measure guidance
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Information Theoretic Measure for Visual Target Distinctness
IEEE Transactions on Pattern Analysis and Machine Intelligence
Wavelet-based corner detection technique using optimal scale
Pattern Recognition Letters
Distributed recursive learning for shape recognition through multiscale trees
Image and Vision Computing
An adaptive window mechanism for image smoothing
Computer Vision and Image Understanding
Scale detection via keypoint density maps in regular or near-regular textures
Pattern Recognition Letters
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This paper analyzes how the natural scales of the shapes in 2D images can be extracted. Spatial information is analyzed by multiple units sensitive to both spatial and spatial-frequency variables. Scale estimates of the relevant shapes are constructed only from strongly responding detectors. The meaningful structures in the response of a detector (computed through 2D Gabor filtering) are, at their natural level of resolution, relatively sharp and have well-defined boundaries. A natural scale is so defined as a level 驴 producing local minimum of a function that returns the relative sharpness of the detector response filtered over a range of scales. In a second stage, to improve a first crude estimate of the local scale, the criterion is also rewritten to directly select scales at locations of significant features of each activated detector.