Ridges in Image and Data Analysis (Computational Imaging and by D. Eberly

By D. Eberly

This e-book offers an intensive improvement of ridges and their software to snapshot and knowledge research. The textual content is self-contained through together with a bankruptcy at the invaluable mathematical historical past, chapters at the formal ridge definitions in any geometric environment, and a bankruptcy at the numerical implementation. An purposes bankruptcy covers 3 separate issues: scientific photo research, molecular modeling, and research of fluid movement. viewers: The e-book is meant essentially for laptop imaginative and prescient and snapshot processing scientists with a historical past in arithmetic and medical computation. although, ridges offer a normal objective device for multidimensional information research, so the publication can be of curiosity to practitioners in any box which calls for the studying of knowledge, such as records, the actual sciences, or engineering.

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By D. Eberly

This e-book offers an intensive improvement of ridges and their software to snapshot and knowledge research. The textual content is self-contained through together with a bankruptcy at the invaluable mathematical historical past, chapters at the formal ridge definitions in any geometric environment, and a bankruptcy at the numerical implementation. An purposes bankruptcy covers 3 separate issues: scientific photo research, molecular modeling, and research of fluid movement. viewers: The e-book is meant essentially for laptop imaginative and prescient and snapshot processing scientists with a historical past in arithmetic and medical computation. although, ridges offer a normal objective device for multidimensional information research, so the publication can be of curiosity to practitioners in any box which calls for the studying of knowledge, such as records, the actual sciences, or engineering.

Show description

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S. Peirce to S. Watanabe and spanning a century, one finds proofs that similarity can be anything you likeunless a system of observer-imposed biases intervenes to remove the uncertainty.  A theoretical framework for this approach to representation, a computational model, its implementation, testing, and examination in the light of neurobiological and psychophysical data, are described in chapters 3 through 6. Page xix similarity claim that an ellipsoid (for example) is more similar to a sphere than to a cube only as long as somebody sufficiently like us is watching it.

The current notion of feature detection differs from the classical one in two respects. First, it is now clear that the representational power of an ensemble of feature detectors may far exceed that of any of its constituents alone. Second, many theoreticians have realized that "symbolic" or combinatorial composition is not the only way to put various features together. Consider as an example the problem of specifying a representation for spatial discrimination tasks such as vernier acuity. In a typical instance of this task, human subjects routinely discriminate between left and right offsets of two abutting vertical line segments, even when the size of the offset is much smaller than the spacing of the photoreceptors in the fovea centralis (Westheimer, 1981).

A major goal of this book is to explore the possibility Page 17 of an alternative approach to the representation of structure of shapes, which would support compositionality and productivity without relying on explicit syntactic analysis or manipulation.

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