7 papers · 1 filter
Fractal measures of image local features: an application to texture recognition
Pedro M. Silva, Joao B. Florindo
Here we propose a new method for the classification of texture images combining fractal measures (fractal dimension, multifractal spectrum and lacunarity) with local binary pattern…
VisGraphNet: a complex network interpretation of convolutional neural features
Joao B. Florindo, Young-Sup Lee, Kyungkoo Jun +2
Here we propose and investigate the use of visibility graphs to model the feature map of a neural network. The model, initially devised for studies on complex networks, is employed…
An application of a pseudo-parabolic modeling to texture image recognition
Joao B. Florindo, Eduardo Abreu
In this work, we present a novel methodology for texture image recognition using a partial differential equation modeling. More specifically, we employ the pseudo-parabolic Buckley…
Texture image classification based on a pseudo-parabolic diffusion model
Jardel Vieira, Eduardo Abreu, Joao B. Florindo
This work proposes a novel method based on a pseudo-parabolic diffusion process to be employed for texture recognition. The proposed operator is applied over a range of time scales…
A cellular automata approach to local patterns for texture recognition
Joao Florindo, Konradin Metze
Texture recognition is one of the most important tasks in computer vision and, despite the recent success of learning-based approaches, there is still need for model-based solution…
Reorganizing local image features with chaotic maps: an application to texture recognition
Joao Florindo
Despite the recent success of convolutional neural networks in texture recognition, model-based descriptors are still competitive, especially when we do not have access to large am…