Person:
López Molina, Carlos

Profile Picture

Email Address

person.page.identifierURI

https://academica-e.unavarra.es/handle/2454/49448

Birth Date

Research Projects

Organizational Units

Job Title

Last Name

López Molina

First Name

Carlos

person.page.departamento

Estadística, Informática y Matemáticas

person.page.instituteName

ORCID

0000-0002-0904-9834

person.page.upna

810097

Name

Filters

20191
Reset filters

Settings

Author: Baets, Bernard de × Author: López Molina, Carlos × End date: 2019 ×

Search Results

Now showing 1 - 1 of 1
  • Thumbnail Image
    PublicationOpen Access
    Multiscale edge detection using first-order derivative of anisotropic Gaussian kernels
    (Springer, 2019) Wang, Gang; López Molina, Carlos; Baets, Bernard de; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
    Spatially scaled edges are ubiquitous in natural images. To better detect edges with heterogeneous widths, in this paper, we propose a multiscale edge detection method based on first-order derivative of anisotropic Gaussian kernels. These kernels are normalized in scale-space, yielding a maximum response at the scale of the observed edge, and accordingly, the edge scale can be identified. Subsequently, the maximum response and the identified edge scale are used to compute the edge strength. Furthermore, we propose an adaptive anisotropy factor of which the value decreases as the kernel scale increases. This factor improves the noise robustness of small-scale kernels while alleviating the anisotropy stretch effect that occurs in conventional anisotropic methods. Finally, we evaluate our method on widely used datasets. Experimental results validate the benefits of our method over the competing methods.