activity
20092025
most citedA systematic comparison of supervised classifiers

227 citations · 794 across the 65 of their papers we have counts for

collaborators
Showing 2014 · cs.CVShow all

7 papers · 2 filters

cs.CV2014★ 28 cited

Texture analysis by multi-resolution fractal descriptors

João B. Florindo, Odemir M. Bruno

This work proposes a texture descriptor based on fractal theory. The method is based on the Bouligand-Minkowski descriptors. We decompose the original image recursively into 4 equa…

cs.CV2014★ 27 cited

Improved texture image classification through the use of a corrosion-inspired cellular automaton

Núbia Rosa da Silva, Pieter Van der Weeën, Bernard De Baets +1

In this paper, the problem of classifying synthetic and natural texture images is addressed. To tackle this problem, an innovative method is proposed that combines concepts from co…

cs.CV2014★ 54 cited

Gabor wavelets combined with volumetric fractal dimension applied to texture analysis

Álvaro Gomez Z., João B. Florindo, Odemir M. Bruno

Texture analysis and classification remain as one of the biggest challenges for the field of computer vision and pattern recognition. On this matter, Gabor wavelets has proven to b…

cs.CV2014★ 12 cited

Fractal descriptors based on the probability dimension: a texture analysis and classification approach

João Batista Florindo, Odemir Martinez Bruno

In this work, we propose a novel technique for obtaining descriptors of gray-level texture images. The descriptors are provided by applying a multiscale transform to the fractal di…

cs.CV2014★ 30 cited

Brachiaria species identification using imaging techniques based on fractal descriptors

João Batista Florindo, Núbia Rosa da Silva, Liliane Maria Romualdo +4

The use of a rapid and accurate method in diagnosis and classification of species and/or cultivars of forage has practical relevance, scientific and trade in various areas of study…

cs.CV2014★ 30 cited

Texture analysis using volume-radius fractal dimension

André R. Backes, Odemir M. Bruno

Texture plays an important role in computer vision. It is one of the most important visual attributes used in image analysis, once it provides information about pixel organization…