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Multifractals, texture, and image analysis

Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003
Image analysis using texture and multifractal paradigms is addressed. Multifractal theory and its application to image description are discussed, and it is shown that this approach allows the discrete signal to be worked on directly. A system for texture classification that is based on a learning scheme and does not make use of any a priori model is ...
Lévy Véhel, Jacques, Mignot, P., Berroir, Jean-Paul   +2 more
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Image retrieval by shape and texture

Pattern Recognition, 1999
Abstract Effective image retrieval by content from database requires that visual image properties are used instead of textual labels to recover pictorial data. Retrieval by image similarity given a template image is particularly challenging. The difficulty is to derive a similarity measure that combines shape, grey level patterns and texture in a way
PALA, PIETRO, S. SANTINI
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Image Texture, Texture Features, and Image Texture Classification and Segmentation

2019
In this chapter, we will discuss the basic concept of image texture, texture features, and image texture classification and segmentation. These concepts will be the foundation to understand image texture models and algorithms used for image texture analysis.
Chih-Cheng Hung, Enmin Song, Yihua Lan
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Complexity Perception of Texture Images

2015
Visual complexity perception plays an important role in the fields of both psychology and computer vision: it can be useful not only to investigate human perception but also to better understand the properties of the objects being perceived. In this paper we investigate the complexity perception of texture images.
CIOCCA, GIANLUIGI, CORCHS, SILVIA ELENA, GASPARINI, FRANCESCA   +2 more
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Saliency Detection in Textured Images

2020 15th International Conference on Computer Science & Education (ICCSE), 2020
Recently, salient object detection has achieved significant development. Unfortunately, existing methods mainly depend on color differences, not effective for textured images. This is because the visual patterns of textures cannot be well measured with existing methods.
Yu Zeng, Biyu Wan
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Turbo Segmentation of Textured Images

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011
We consider the problem of semi-supervised segmentation of textured images. Existing model-based approaches model the intensity field of textured images as a Gauss-Markov random field to take into account the local spatial dependencies between the pixels. Classical Bayesian segmentation consists of also modeling the label field as a Markov random field
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Texture models and image measures for texture discrimination

International Journal of Computer Vision, 1989
The task of texture segmentation is to identify image curves that separate different textures. To segment textured images, one must first be able to discriminate textures. A segmentation algorithm performs texture-discrimination tests at densely spaced image positions, then interprets the results to localize edges.
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Image retrieval by texture similarity

Pattern Recognition, 2003
Accuracy and efficiency are the two important issues in designing content-based image retrieval systems. In this paper, we present an efficient image retrieval system with high performance of accuracy based on two novel features, the composite sub-band gradient vector and the energy distribution pattern string.
Po-Whei Huang, S. K. Dai
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Texture-Preserving Image Deblurring

IEEE Signal Processing Letters, 2010
In this letter, a two-step texture-preserving image deblurring method is proposed. This method restores the blurred image in the frequency domain to obtain a noisy result with minimal loss of signal components, followed by a modified non-local means (NLM) filter to attenuate the leaked colored noise.
Fen Chen, Xiaojun Huang, Wufan Chen
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Image segmentation by texture analysis

Proceedings 10th International Conference on Image Analysis and Processing, 2003
Texture segmentation is a significant and primary issue in texture analysis. It is concerned with automatically determining the boundaries between various textured regions in an image. In this paper we propose a region-based method for textured image segmentation. First, we consider the basic problem of texel identification and the determination of its
DI RUBERTO, CECILIA, RODRIGUEZ, GIUSEPPE, VITULANO S.   +2 more
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