Results 261 to 270 of about 151,882 (297)

Soft local binary patterns

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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Similarity assessment with local binary patterns

2012 20th Signal Processing and Communications Applications Conference (SIU), 2012
Identification 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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Number Local binary pattern: An Extended Local Binary Pattern

2011 International Conference on Wavelet Analysis and Pattern Recognition, 2011
An 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, 2018
Several 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, Abdeljalil Gattal, Mohamed Ridda Laouar, Kamel Saoudi, Ismail Hadjadj   +4 more
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Discriminative local binary pattern

Machine Vision and Applications, 2016
Local 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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A Bayesian Local Binary Pattern texture descriptor

2008 19th International Conference on Pattern Recognition, 2008
In 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), 2016
Texture 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, Mehmet Koç, Burak Benligiray, Cihan Topal   +3 more
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Face Recognition with Local Binary Patterns

2004
In this work, we present a novel approach to face recognition which considers both shape and texture information to represent face images. The face area is first divided into small regions from which Local Binary Pattern (LBP) histograms are extracted and concatenated into a single, spatially enhanced feature histogram efficiently representing the face
Timo Ahonen, Abdenour Hadid, Matti Pietikäinen   +2 more
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A local feature descriptor based on Local Binary Patterns

2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2016
This paper presents a local feature descriptor based on Local Binary Patterns (LBP). This descriptor uses binary bit string to represent the local region of images and the integral image to mean filter that makes descriptor building faster. Compared to Scale-invariant feature transform (SIFT)that the calculation is large and the process is time ...
Gaoqing Cheng, Jiaxing Chen
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Weight-Optimal Local Binary Patterns

2015
In this work, we have proposed a learning paradigm for obtaining weight-optimal local binary patterns (WoLBP). We first re-formulate the LBP problem into matrix multiplication with all the bitmaps flattened and then resort to the Fisher ratio criterion for obtaining the optimal weight matrix for LBP encoding.
Felix Juefei-Xu, Marios Savvides
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