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Journal ArticleDOI

Choice of a pertinent color space for color texture characterization using parametric spectral analysis

TLDR
A comparison of different color spaces including RGB, IHLS and [email protected]?a*b* for color texture characterization is presented and experimental results on pixel classification of color textures are presented and discussed.
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This article is published in Pattern Recognition.The article was published on 2011-01-01. It has received 50 citations till now. The article focuses on the topics: RGB color model & Color space.

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Citations
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Journal ArticleDOI

Color texture analysis based on fractal descriptors

TL;DR: The proposed approach investigates the complexity in R, G and B color channels to characterize a texture sample and proposes to study all channels in combination, taking into consideration the correlations between them.
Journal ArticleDOI

Influence of normalization and color space to color texture classification

TL;DR: An exhaustive evaluation of the state-of-the-art color texture classification methods, considering 5 different color spaces, 12 normalization methods to achieve illumination invariances, 19 texture feature vectors and 23 pure color feature vectors concludes that parallel approaches are better than integrative approaches for color texture classified achieving the first positions in the Friedman ranking.
Journal ArticleDOI

Comparative Evaluation of Hand-Crafted Image Descriptors vs. Off-the-Shelf CNN-Based Features for Colour Texture Classification under Ideal and Realistic Conditions

TL;DR: Traditional, hand-crafted descriptors were better at discriminating stationary textures under steady imaging conditions and proved more robust than CNN-based features to image rotation, indicating a marked superiority of deep networks with non-stationary textures and in the presence of multiple changes in the acquisition conditions.

A Survey on Content Based Image Retrieval

TL;DR: This survey covers approaches used for extracting low level features; various distance measures for measuring the similarity of images, the mechanisms for reducing the semantic gap and about invariant image retrieval.
Journal ArticleDOI

Performance analysis of colour descriptors for parquet sorting

TL;DR: Simple and compact colour descriptors, such as the mean of each colour channel, are as accurate as more complicated features and the use of simple statistical descriptors along with RGB data as the best practice to approach the problem is suggested.
References
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Journal ArticleDOI

Multiresolution gray-scale and rotation invariant texture classification with local binary patterns

TL;DR: A generalized gray-scale and rotation invariant operator presentation that allows for detecting the "uniform" patterns for any quantization of the angular space and for any spatial resolution and presents a method for combining multiple operators for multiresolution analysis.
Journal ArticleDOI

Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions

TL;DR: This paper presents convergence properties of the Nelder--Mead algorithm applied to strictly convex functions in dimensions 1 and 2, and proves convergence to a minimizer for dimension 1, and various limited convergence results for dimension 2.
Proceedings ArticleDOI

Approximating the Kullback Leibler Divergence Between Gaussian Mixture Models

TL;DR: Two new methods, the variational approximation and the Variational upper bound, are introduced and compared to existing methods and the benefits of each one are considered and the performance of each is evaluated through numerical experiments.
Proceedings ArticleDOI

Outex - new framework for empirical evaluation of texture analysis algorithms

TL;DR: The proposed Outex framework contains a large collection of surface textures captured under different conditions, which facilitates construction of a wide range of texture analysis problems.
Journal ArticleDOI

Distance measures for signal processing and pattern recognition

TL;DR: Some classical results about error bounds in classification and feature selection for pattern recognition are recalled, which are obtained with the aid of properties of distance measures.
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