Journal ArticleDOI
A mathematical approach to edge detection in hyperbolic-distributed and Gaussian-distributed pixel-intensity images using hyperbolic and Gaussian masks
Reads0
Chats0
TLDR
A new hyperbolic distribution andhyperbolic mask for edge detection is introduced and edge-detection error probability as a function of the half mask size m is estimated using both masks in Gaussian- andHyperbolic-distributed pixel-intensity images.About:
This article is published in Digital Signal Processing.The article was published on 2011-01-01. It has received 23 citations till now. The article focuses on the topics: Hyperbolic distribution & Generalized inverse Gaussian distribution.read more
Citations
More filters
Journal ArticleDOI
Multiscale patch-based contrast measure for small infrared target detection
Yantao Wei,Xinge You,Hong Li +2 more
TL;DR: Experimental results on three sequences demonstrate that the proposed small target detection method can not only suppress background clutter effectively even if with strong noise interference, but also detect targets accurately with low false alarm rate and high speed.
Journal ArticleDOI
Fractional Fourier Transform and Fractional-Order Calculus-Based Image Edge Detection
TL;DR: This paper demonstrates a new kind of edge detector based on the ‘fractional’ (‘non-integer’)-order differentiation operation and through the usage of the ’fractionale Fourier transformation’ tool, so as to perform it in the fractional Fourier frequency domain, known as the edge detection based on fractional signal processing approach.
Journal ArticleDOI
Active cleaning of label noise
Rajmadhan Ekambaram,Sergiy Fefilatyev,Matthew Shreve,Kurt Kramer,Lawrence O. Hall,Dmitry B. Goldgof,Rangachar Kasturi +6 more
TL;DR: This paper proposes another new method that iteratively builds two-class SVM classifiers on the non-support vector examples from the training data followed by an expert manually verifying the support vectors based on their classification score to identify any mislabeled examples.
Journal ArticleDOI
Robust face recognition after plastic surgery using region-based approaches
TL;DR: Experimental results show that the proposed methods yield much better performance than state-of-the art algorithms, both holistic and region based, in addressing face recognition after plastic surgery.
Journal ArticleDOI
Optimizing the Gaussian kernel function with the formulated kernel target alignment criterion for two-class pattern classification
TL;DR: A novel fast method to optimize the Gaussian kernel function for two-class pattern classification tasks, where it is desirable for the kernel machines to use an optimized kernel that adapts well to the input data and the learning tasks.
References
More filters
Book
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
TL;DR: Marr's posthumously published Vision (1982) influenced a generation of brain and cognitive scientists, inspiring many to enter the field of visual perception as discussed by the authors, where the process of vision constructs a set of representations, starting from a description of the input image and culminating with three-dimensional objects in the surrounding environment, a central theme and one that has had farreaching influence in both neuroscience and cognitive science, is the notion of different levels of analysis.
Book
Advanced Engineering Mathematics
TL;DR: This book discusses ODEs, Partial Differential Equations, Fourier Series, Integrals, and Transforms, and Numerics for ODE's and PDE's, as well as numerical analysis and potential theory, and more.
Journal ArticleDOI
Advanced Engineering Mathematics.
Ronald F. Barnes,Erwin Kreyszig +1 more
TL;DR: In this article, the authors present an approach for ODE's Phase Plane, Qualitative Methods, and Partial Differential Equations (PDE's) to solve ODE problems.
Journal ArticleDOI
Vision. A Computational Investigation Into the Human Representation and Processing of Visual Information. David Marr
Journal ArticleDOI
Improved time-frequency representation of multicomponent signals using exponential kernels
H.-I. Choi,William J. Williams +1 more
TL;DR: In this article, a time-frequency distribution of L. Cohen's (1966) class is introduced, which is called exponential distribution (ED) after its exponential kernel function, and the authors interpret the ED from the spectral density-estimation point of view.