Book ChapterDOI
Pyramid-based multi-structure local binary pattern for texture classification
Yonggang He,Nong Sang,Changxin Gao +2 more
- pp 133-144
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TLDR
The drawback of conventional LBP operators in describing some textures that has the same small structures but differential large structures is investigated and a multi-structure local binary pattern operator is achieved by executing the LBP method on different layers of image pyramid.Abstract:
Recently, the local binary pattern (LBP) has been widely used in texture classification. The conventional LBP methods only describe micro structures of texture images, such as edges, corners, spots and so on, although many of them show a good performance on texture classification. This situation still could not be changed, even though the multiresolution analysis technique is used in methods of local binary pattern. In this paper, we investigate the drawback of conventional LBP operators in describing some textures that has the same small structures but differential large structures. And a multi-structure local binary pattern operator is achieved by executing the LBP method on different layers of image pyramid. The proposed method is simple yet efficient to extract not only the micro structures but also the macro structures of texture images. We demonstrate the performance of our method on the task of rotation invariant texture classification. The experimental results on Outex database show advantages of the proposed method.read more
Citations
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Book ChapterDOI
Local Binary Patterns for Still Images
TL;DR: This chapter provides an in-depth description of the LBP operator in spatial image domain, and its rotation-invariant and multiscale versions are introduced.
Book ChapterDOI
Two decades of local binary patterns: A survey
Matti Pietikäinen,Guoying Zhao +1 more
TL;DR: In this chapter, the most recent and important variants of LBP in 2- D, spatiotemporal, 3-D, and 4-D domains are surveyed and some future challenges for research are presented.
Journal ArticleDOI
Research and Perspective on Local Binary Pattern
TL;DR: In view of the theoretical and practical value of local binary pattern (LBP), the various LBP methods in texture analysis and classification, face analysis and recognition, and other detection applications are reviewed.
Journal ArticleDOI
Rotation–Covariant Texture Learning Using Steerable Riesz Wavelets
TL;DR: A texture learning approach that exploits local organizations of scales and directions that requires no arbitrary choices of scales or directions and is expected to perform well in a large range of computer vision applications.
Journal ArticleDOI
Image-Based Delineation and Classification of Built Heritage Masonry
TL;DR: The ground work carried out to make this tool possible is presented: the automatic, image-based delineation of stone masonry as the input to a classifier for a geometrically characterized feature of a built heritage object.
References
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Journal ArticleDOI
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
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
A comparative study of texture measures with classification based on featured distributions
TL;DR: This paper evaluates the performance both of some texture measures which have been successfully used in various applications and of some new promising approaches proposed recently.
Journal ArticleDOI
Texture features for browsing and retrieval of image data
B.S. Manjunath,Wei-Ying Ma +1 more
TL;DR: Comparisons with other multiresolution texture features using the Brodatz texture database indicate that the Gabor features provide the best pattern retrieval accuracy.
Journal ArticleDOI
Filtering for texture classification: a comparative study
Trygve Randen,John Hakon Husoy +1 more
TL;DR: Most major filtering approaches to texture feature extraction are reviewed and a ranking of the tested approaches based on extensive experiments is presented, showing the effect of the filtering is highlighted, keeping the local energy function and the classification algorithm identical for most approaches.