Results 41 to 50 of about 1,054,370 (330)

Local binary pattern domain local appearance face recognition

open access: yes2008 IEEE 16th Signal Processing, Communication and Applications Conference, 2008
This paper presents a fast face recognition algorithm that combines the discrete cosine transform based local appearance face recognition technique with the local binary pattern (LBP) representation of the face images. The underlying idea is to benefit from both the robust image representation capability of local binary patterns, and the compact ...
Ekenel, H. K.   +4 more
openaire   +3 more sources

Dominant Local Binary Patterns for Texture Classification [PDF]

open access: yesIEEE Transactions on Image Processing, 2009
This paper proposes a novel approach to extract image features for texture classification. The proposed features are robust to image rotation, less sensitive to histogram equalization and noise. It comprises of two sets of features: dominant local binary patterns (DLBP) in a texture image and the supplementary features extracted by using the circularly
Liao, Shu   +2 more
openaire   +3 more sources

Finger Vein Recognition Based on Local Directional Code

open access: yesSensors, 2012
Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network.
Rongyang Xiao   +3 more
doaj   +1 more source

Feature Descriptor Based on Local Binary Pattern with Equidistant Ring [PDF]

open access: yesJisuanji gongcheng, 2017
Existing descriptors are generally associated with principal direction.When the images are transformed,deviation usually occurs in the principal direction of the descriptors,which leads to unsatisfactory image matching results.In order to solve this ...
YU Qiang,NIE Hongyu,ZHANG Jingjing
doaj   +1 more source

Scale Selective Extended Local Binary Pattern for Texture Classification

open access: yes, 2018
In this paper, we propose a new texture descriptor, scale selective extended local binary pattern (SSELBP), to characterize texture images with scale variations.
AlRegib, Ghassan   +2 more
core   +1 more source

Generalized local N-ary patterns for texture classification [PDF]

open access: yes, 2013
Local Binary Pattern (LBP) has been well recognised and widely used in various texture analysis applications of computer vision and image processing. It integrates properties of texture structural and statistical texture analysis.
He, X, Wang, S, Wu, Q, Yang, J
core   +1 more source

Quantifying appearance retention in carpets using geometrical local binary patterns [PDF]

open access: yes, 2011
Quality assessment in carpet manufacturing is performed by humans who evaluate the appearance retention (AR) grade on carpet samples. To quantify the AR grades objectively, different research based on computer vision have been developed. Among them Local
E. Wood   +12 more
core   +1 more source

Deep Learning in Face Recognition for Attendance System: An Exploratory Study

open access: yesJournal of Computing Research and Innovation, 2022
Conventional-manual type of attendance systems can be very time-consuming to some extent, particularly for a significant number. The existence of face recognition technology can solve the inefficiency and ineffectiveness of conventional and manual ...
Mochamad Azkal Azkiya Aziz   +2 more
doaj   +3 more sources

Automatic nesting seabird detection based on boosted HOG-LBP descriptors [PDF]

open access: yes, 2011
Seabird populations are considered an important and accessible indicator of the health of marine environments: variations have been linked with climate change and pollution 1.
Dickinson, Patrick   +3 more
core   +1 more source

Local Binary Pattern Networks

open access: yes, 2018
Memory and computation efficient deep learning architec- tures are crucial to continued proliferation of machine learning capabili- ties to new platforms and systems. Binarization of operations in convo- lutional neural networks has shown promising results in reducing model size and computing efficiency.
Lin, Jeng-Hau   +3 more
openaire   +2 more sources

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