A discriminant color space method for face representation and verification on a large-scale database

2008 ◽  
Author(s):  
Jian Yang ◽  
Chengjun Liu
Keyword(s):  
Large Scale ◽  
Color Space ◽  
Face Representation ◽  
Space Method

Study on space absorbing of multilayer MWCNTs/Fe3O4/NBR composites

2021 ◽  
pp. 2150112
Author(s):  
Song Xinhua ◽  
Zhou Haiyang ◽  
Zhao Tiejun ◽  
Li Xiaojie ◽  
Yan Honghao
Keyword(s):  
Reflection Loss ◽  
Free Space ◽  
Large Scale ◽  
Comsol Multiphysics ◽  
Maximum Value ◽  
The Matrix ◽  
Attenuation Loss ◽  
Stealth Materials ◽  
Free Space Method ◽  
Space Method

In order to meet the requirements of “wide, thin, strong and light” for military stealth materials, it is of great practical value to study the absorbing characteristics of multi-layer MWCNTs/Fe3O4/NBR absorbing materials in space. First, we use the large-scale software COMSOL Multiphysics to simulate the absorbing characteristics of the composite thin plate in space. Then the four-port network matrix is used to calculate the absorbing characteristics of the composite plate in space. Finally, the Free-Space method is used to measure the reflection attenuation loss, and the results of the three methods are compared and analyzed. The results show that when the frequency is 10 GHz, the reflection loss of multi-layer MWCNTs/Fe3O4/NBR reaches the maximum value of −27.91, −27.01 and −22.56 dB by COMOSL numerical simulation, four-port network the matrix and Free-Space experimental measurement. The results of the three methods show that the reflection loss is less than −10 dB in the frequency band of 6–14 GHz.

A k-space method for large-scale models of wave propagation in tissue

2001 ◽  
Vol 48 (2) ◽  
pp. 341-354 ◽  
Author(s):  
T.D. Mast ◽  
L.P. Souriau ◽  
D.-L.D. Liu ◽  
M. Tabei ◽  
A.I. Nachman ◽  
...  
Keyword(s):  
Wave Propagation ◽  
Large Scale ◽  
Scale Models ◽  
Space Method

All-Sky Cloud Classification Based on Transparency and Texture Features

2012 ◽  
Vol 235 ◽  
pp. 3-8
Author(s):  
Xiao Ying Chen ◽  
Min Wang ◽  
Shu Dao Zhou
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Recognition Rate ◽  
Color Space ◽  
Texture Features ◽  
Experimental Results ◽  
Second Moment ◽  
Cloud Classification ◽  
Space Method ◽  
Classification Recognition

This paper proposes a new algorithm to classify the cloud of all-sky ground-based based on transparency and texture features. First, we uses the transparency to separate the single sky background and cloud foreground image, which based on the natural matting of perceptual color space method, then analysis the texture features of cloud foreground image with second moment, contrast, correlation and entropy, finally, uses BP neural network to identify the type of the cloud. The experimental results show that the algorithm can separate the sky and cloud effectively, and the cloud classification recognition rate is higher.

Application of Multiport Video Interface Controller to Banknote Checking

2013 ◽  
Vol 339 ◽  
pp. 114-117
Author(s):  
Qing Wang Qin ◽  
Jian Zhang ◽  
Zhi Guo Feng ◽  
Feng Li ◽  
Jun Hua Sui
Keyword(s):  
High Speed ◽  
High Performance ◽  
Large Scale ◽  
Color Space ◽  
Detection Algorithm ◽  
Video Data ◽  
Reliable Performance ◽  
Sorting System ◽  
Interface Parameters ◽  
Video Interface

To the banknote sorting system, application of large-scale high-performance FPGA can help to conduct high speed capture and processing of banknote color images. In line with the detection algorithm, the real-time-captured image upon color-space conversion needs to be compared in the four color channels of LGAB with the template images so as to work out the checking results. With Xilinx soft IP core MPMC, two sets of multiport video interface controllers have been designed, each of which embraces four ways of video data read-write operation; the controller interface parameters can be configured via the DSP interface, with the process flow control based on the image frame synchronizing signal. Tests conducted show that the controllers with flexible configurations boast of reliable performance and now are reputed for proven application to large banknote sorting equipment.

scholarly journals A Novel Image Classification Approach for Maize Diseases Recognition

2020 ◽  
Vol 13 (3) ◽  
pp. 331-339
Author(s):  
Yuchen Wei ◽  
Lisheng Wei ◽  
Tao Ji ◽  
Huosheng Hu
Keyword(s):  
Image Classification ◽  
Large Scale ◽  
Clustering Algorithm ◽  
Color Space ◽  
Support Vector ◽  
Classification Approach ◽  
Large Scale Data ◽  
Lab Color Space ◽  
Occurrence Matrix ◽  
Future Work

Background: The spot, streak and rust are the most common diseases in maize, all of which require effective methods to recognize, diagnose and handle. This paper presents a novel image classification approach to the high accuracy recognition of these maize diseases. Methods: Firstly, the k-means clustering algorithm is deployed in LAB color space to reduce the influence of image noise and irrelevant background, so that the area of maize diseases could be effectively extracted. Then the statistic pattern recognition method and gray level co-occurrence matrix (GLCM) method are jointly used to segment the maize disease leaf images for accurately obtaining their texture, shape and color features. Finally, Support Vector Machine (SVM) classification method is used to identify three diseases. Results: Numerical results clearly demonstrate the feasibility and effectiveness of the proposed method. Conclusion: Our future work will focus on the investigation of how to use the new classification methods in dimensional and large scale data to improve the recognizing performance and how to use other supervised feature selection methods to improve the accuracy further.

scholarly journals Genetic Analysis of Walnut (Juglans regia L.) Pellicle Pigment Variation Through a Novel, High-Throughput Phenotyping Platform

2020 ◽  
Vol 10 (12) ◽  
pp. 4411-4424
Author(s):  
Gina M. Sideli ◽  
Peter McAtee ◽  
Annarita Marrano ◽  
Brian J. Allen ◽  
Patrick J. Brown ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Juglans Regia ◽  
Color Space ◽  
Consumer Preference ◽  
Improvement Program ◽  
Genome Wide ◽  
A Genome ◽  
High Throughput Phenotyping ◽  
Pigment Variation

Walnut pellicle color is a key quality attribute that drives consumer preference and walnut sales. For the first time a high-throughput, computer vision-based phenotyping platform using a custom algorithm to quantitatively score each walnut pellicle in L* a* b* color space was deployed at large-scale. This was compared to traditional qualitative scoring by eye and was used to dissect the genetics of pellicle pigmentation. Progeny from both a bi-parental population of 168 trees (‘Chandler’ × ‘Idaho’) and a genome-wide association (GWAS) with 528 trees of the UC Davis Walnut Improvement Program were analyzed. Color phenotypes were found to have overlapping regions in the ‘Chandler’ genetic map on Chr01 suggesting complex genetic control. In the GWAS population, multiple, small effect QTL across Chr01, Chr07, Chr08, Chr09, Chr10, Chr12 and Chr13 were discovered. Marker trait associations were co-localized with QTL mapping on Chr01, Chr10, Chr14, and Chr16. Putative candidate genes controlling walnut pellicle pigmentation were postulated.

scholarly journals A numerical simulation method for a repairable dynamic fault tree

2021 ◽  
Vol 23 (1) ◽  
pp. 34-41
Author(s):  
Zhixin Xu ◽  
Dingqing Guo ◽  
Jinkai Wang ◽  
Xueli Li ◽  
Daochuan Ge
Keyword(s):  
Markov Chain ◽  
State Space ◽  
Large Scale ◽  
Fault Tree ◽  
Simulation Method ◽  
Time To Failure ◽  
State Space Method ◽  
Dynamic Fault Tree ◽  
Distributed Components ◽  
Space Method

Dynamic fault trees are important tools for modeling systems with sequence failure behaviors. The Markov chain state space method is the only analytical approach for a repairable dynamic fault tree (DFT). However, this method suffers from state space explosion, and is not suitable for analyzing a large scale repairable DFT. Furthermore, the Markov chain state space method requires the components’ time-to-failure to follow exponential distributions, which limits its application. In this study, motivated to efficiently analyze a repairable DFT, a Monte Carlo simulation method based on the coupling of minimal cut sequence set (MCSS) and its sequential failure region (SFR) is proposed. To validate the proposed method, a numerical case was studied. The results demonstrated that our proposed approach was more efficient than other methods and applicable for repairable DFTs with arbitrary time-to-failure distributed components. In contrast to the Markov chain state space method, the proposed method is straightforward, simple and efficient.

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