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Local Binary Patterns of Segments of a Binary Object for Shape Analysis
Journal of Mathematical Imaging and Vision, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ratnesh Kumar, Kalyani Mali
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2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR), 2015
Local Binary Pattern (LBP) is known as one of the most effective local descriptors for image recognition. It is invariant to monotonic gray-scale changes of the image. Local neighborhood information is gathered for each pixel of the image, and a binary code is generated by comparing its value with the value of the center pixel.
Ran Li, Xuezhen Li, Takio Kurita
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Local Binary Pattern (LBP) is known as one of the most effective local descriptors for image recognition. It is invariant to monotonic gray-scale changes of the image. Local neighborhood information is gathered for each pixel of the image, and a binary code is generated by comparing its value with the value of the center pixel.
Ran Li, Xuezhen Li, Takio Kurita
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Similarity assessment with local binary patterns
2012 20th Signal Processing and Communications Applications Conference (SIU), 2012Identification from human face plays an important role in social interaction, such as recognition and security. Thus facial information processing is an active research area in pattern recognition. The similarity of a child's face to parent faces is evaluated in this paper.
Vasif V. Nabiyev, Beste Gencturk
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Structured local binary Haar pattern for pixel-based graphics retrieval
National Nature Science Foundation of China [60873179]; Shenzhen Technology Fundamental Research [JC200903180630A]; Doctoral Program Foundation of Institutions of Higher Education of China [20090121110032]A feature, named structured local binary Haar ...
Li, S. A. +11 more
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Number Local binary pattern: An Extended Local Binary Pattern
2011 International Conference on Wavelet Analysis and Pattern Recognition, 2011An extension of local binary pattern, named Number Local binary pattern (NLBP), is presented for texture analysis. First, the method divides the patterns into uniform and non-uniform according to the uniform measure. Second, the non-uniform pattern is further divided into different groups based on the numbers of ‘1’ bits and ‘0’ bits.
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Local Binary Patterns for Gender Classification
Proceedings of the 7th International Conference on Software Engineering and New Technologies, 2018Several approaches for gender of handwriting are proposed an appearance feature-based approach. In this paper we present a comparative study to evaluate effectiveness of different Local Binary Patterns methodologies in characterizing gender from handwriting. We investigate different local binary patterns (LBP) parameters with/without preprocessing step
Faycel Abbas +4 more
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Discriminative local binary pattern
Machine Vision and Applications, 2016Local binary pattern (LBP) is widely used to extract image features as well as motion features in various visual recognition tasks. LBP is formulated in quite a simple form and thus enables us to extract effective features with a low computational cost.
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Mixed co-occurrence of local binary patterns and Hamming-distance-based local binary patterns
Information Sciences, 2018Abstract Local binary patterns (LBP) have powerful discriminative capabilities. However, traditional methods with LBP histograms cannot capture spatial structures of LBP codes. To extract the spatial structures of an LBP code map, we compute and encode the Hamming distances between LBP codes of a center point and its neighbors on the LBP code map to ...
Feiniu Yuan, Xue Xia 0005, Jinting Shi
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A Bayesian Local Binary Pattern texture descriptor
2008 19th International Conference on Pattern Recognition, 2008In this paper, a Bayesian LBP operator is proposed. This operator is formulated in a novel filtering, labeling and statistic (FLS) framework for texture descriptors. In the framework, the local labeling procedure, which is a part of many popular descriptors such as LBP, SIFT and VZ, can be modeled as a probability and optimization process. This enables
He Chu, Pietikäinen Matti, Ahonen Timo
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A comparison of classification methods for local binary patterns
2016 24th Signal Processing and Communication Application Conference (SIU), 2016Texture recognition is an important tool used for content-based image retrieval, face recognition, and satellite image classification applications. One of the most successful features for texture recognition is local binary patterns (LBP), which computes local intensity differences for a pixel with respect to its neighbor pixels. In many studies in the
Nihan Kazak +3 more
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