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Found 12 papers, 0 papers with code
Binary Distance Transform to Improve Feature Extraction
This paper proposes the application of binary distance transform on the original dataset to add information to texture representation and consequently improve recognition.
Texture analysis using deterministic partially self-avoiding walk with thresholds
In this paper, we propose a new texture analysis method using the deterministic partially self-avoiding walk performed on maps modified with thresholds.
Fast deterministic tourist walk for texture analysis
Experimental results on the Brodatz and Vistex datasets indicate that to use fewer pixels as initial points significantly improves the runtime compared to use all image pixels.
Improved texture image classification through the use of a corrosion-inspired cellular automaton
In addition, in order to verify the robustness of the method, its invariance to noise and rotation were tested.
Enhancing fractal descriptors on images by combining boundary and interior of Minkowski dilation
The radius of such spheres is ranged within an interval and the volume and the external area of the dilated structure are computed for each radius.
Fractal descriptors based on the probability dimension: a texture analysis and classification approach
In this work, we propose a novel technique for obtaining descriptors of gray-level texture images.
Brachiaria species identification using imaging techniques based on fractal descriptors
Thus, leaf samples of fodder plant species \textit{Brachiaria} were previously identified, collected and scanned to be treated by means of artificial vision to make the database and be used in subsequent classifications.
Satellite image classification and segmentation using non-additive entropy
Here we compare the Boltzmann-Gibbs-Shannon (standard) with the Tsallis entropy on the pattern recognition and segmentation of coloured images obtained by satellites, via "Google Earth".
Texture descriptor combining fractal dimension and artificial crawlers
Since this swarm system alone does not achieve a good discrimination, we developed a new method to increase the discriminatory power of artificial crawlers, together with the fractal dimension theory.
Contour polygonal approximation using shortest path in networks
This paper presents a novel method for polygonal approximation based on the Complex Networks theory.
Heterogeneous patterns enhancing static and dynamic texture classification
To tackle this problem, we propose a method to identify texture patterns not small as textons at distinct scales enhancing the separability among different types of texture.
Multiscale Fractal Descriptors Applied to Texture Classification
This work proposes the combination of multiscale transform with fractal descriptors employed in the classification of gray-level texture images.
