Performing edge detection by difference of Gaussians using q-Gaussian kernels

نویسندگان

  • Lucas Assirati
  • Núbia Rosa da Silva
  • Lilian Berton
  • Alneu de Andrade Lopes
  • Odemir Martinez Bruno
چکیده

X iv :1 31 1. 25 61 v2 [ cs .C V ] 1 2 N ov 2 01 3 Performing edge detection by difference of Gaussians using q-Gaussian kernels Lucas Assirati, Núbia R. da Silva, 2 Lilian Berton, Alneu de A. Lopes, and Odemir M. Bruno 2 Scientific Computing Group, São Carlos Institute of Physics, University of São Paulo (USP), cx 369 13560-970 São Carlos, São Paulo, Brazil www.scg.ifsc.usp.br Institute of Mathematics and Computer Science, University of São Paulo (USP), Avenida Trabalhador são-carlense, 40

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Comparison of Three One-Dimensional Edge Detection Architectures for Analog VLSI Vision Systems

A comparison is made between three architectural models used for edge detection in ;Initlog VLSI early vision systems. In analog VLSI computational networks, signal strength is a paramount issue due to the need to overcome circuit limitations such as offsets, noise, and finite gain. Therefore algorithms mapped into silicon networks must take full advantage of available signal strengths to masim...

متن کامل

A FUZZY DIFFERENCE BASED EDGE DETECTOR

In this paper, a new algorithm for edge detection based on fuzzyconcept is suggested. The proposed approach defines dynamic membershipfunctions for different groups of pixels in a 3 by 3 neighborhood of the centralpixel. Then, fuzzy distance and -cut theory are applied to detect the edgemap by following a simple heuristic thresholding rule to produce a thin edgeimage. A large number of experime...

متن کامل

Noisy images edge detection: Ant colony optimization algorithm

The edges of an image define the image boundary. When the image is noisy, it does not become easy to identify the edges. Therefore, a method requests to be developed that can identify edges clearly in a noisy image. Many methods have been proposed earlier using filters, transforms and wavelets with Ant colony optimization (ACO) that detect edges. We here used ACO for edge detection of noisy ima...

متن کامل

Use of blur-space for deblurring and edge-preserving noise smoothing

The Gaussian blur-space for an unblurred D-image is the set of the images obtained by blurring with multivariate D-Gaussians. Using the variance, instead of the standard deviation, of a Gaussian as blur parameter makes it simpler to extrapolate a deblurred image from a blurred image. Unsharp masking is shown to be a special case of the use of blur-space. Algorithms using blur-space for deblurri...

متن کامل

Bivariate Feature Localization for SIFT Assuming a Gaussian Feature Shape

In this paper, the well-known SIFT detector is extended with a bivariate feature localization. This is done by using function models that assume a Gaussian feature shape for the detected features. As function models we propose (a) a bivariate Gaussian and (b) a Difference of Gaussians. The proposed detector has all properties of SIFT, but provides invariance to affine transformations and blurri...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • CoRR

دوره abs/1311.2561  شماره 

صفحات  -

تاریخ انتشار 2013