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For the purpose of detecting grey-level blobs (local extrema with extent) from a watershed analogy, Lindeberg developed an algorithm based on pre-sorting the pixels, alternatively connected regions having the same intensity, in decreasing order of the intensity values. Then, comparisons were made between nearest neighbours of either pixels or ...
Identify all the local extrema in the test data. Connect all the local maxima by a cubic spline line as the upper envelope. Repeat the procedure for the local minima to produce the lower envelope. The upper and lower envelopes should cover all the data between them. Their mean is m 1. The difference between the data and m 1 is the first ...
By the above equation it is thus clear, that the latter must be the case. Hence ′ = = , so the parameters characterising the local extrema , ′ are identical, which means that the distributions themselves are identical. Thus, the local extreme is unique and by the above discussion, the maximum is unique – provided a local extreme actually ...
The extrema must occur at the pass and stop band edges and at either ω=0 or ω=π or both. The derivative of a polynomial of degree L is a polynomial of degree L−1, which can be zero at most at L−1 places. [3] So the maximum number of local extrema is the L−1 local extrema plus the 4 band edges, giving a total of L+3 extrema.
Corner detection is an approach used within computer vision systems to extract certain kinds of features and infer the contents of an image. Corner detection is frequently used in motion detection, image registration, video tracking, image mosaicing, panorama stitching, 3D reconstruction and object recognition.
The detection and description of local image features can help in object recognition. The SIFT features are local and based on the appearance of the object at particular interest points, and are invariant to image scale and rotation. They are also robust to changes in illumination, noise, and minor changes in viewpoint.
The absolute threshold of hearing is the minimum sound level of a pure tone that an average ear with normal hearing can hear with no other sound present. The absolute threshold relates to the sound that can just be heard by the organism.
In both the global and local cases, the concept of a strict extremum can be defined. For example, x ∗ is a strict global maximum point if for all x in X with x ≠ x ∗, we have f(x ∗) > f(x), and x ∗ is a strict local maximum point if there exists some ε > 0 such that, for all x in X within distance ε of x ∗ with x ≠ x ∗, we ...