scholarly journals A ROBUST BINARIZATION AND TEXT LINE DETECTION IN HISTORICAL HANDWRITTEN DOCUMENTS ANALYSIS

2016 ◽  
pp. 154-161
Author(s):  
Jakub Leszek Pach ◽  
Piotr Bilski
Keyword(s):  
Fifteenth Century ◽  
Hough Transform ◽  
Connected Components ◽  
Image Binarization ◽  
Handwritten Documents ◽  
Local Maxima ◽  
Novel Method ◽  
Block Based ◽  
Binarization Algorithm ◽  
Selection Of

In this paper, we present a novel method of detecting text lines in handwritten documents based on the Block-Based Hough Transform. To maximize its efficiency, the robust binarization algorithm was applied. It is based on the Gaussian filtering and tackles the non-uniform luminance. The proposed technique consists of three steps: preprocessing, detecting of potential text lines and eliminating the false ones. The first step covers the image binarization, extraction of connected components and selection of supporting connected components based on the local maxima in the vertical histogram stripes. Secondly, the appropriate subset of connected components supplemented by one-point components is selected. Finally, the block-based Hough transform is applied to detect potential text lines and found the ones identified incorrectly. The proposed method is applied to the analysis of the fifteenth century Latin manuscripts. Our approach is more effective than the traditional ones, in the best cases by twenty percent.

Classification and Recognition of Plant Leaf Based on Neural Networks

2011 ◽  
Vol 464 ◽  
pp. 38-42 ◽  
Author(s):  
Ping Ye ◽  
Gui Rong Weng
Keyword(s):  
Neural Networks ◽  
Fractal Dimension ◽  
Recognition Rate ◽  
Image Binarization ◽  
Characteristic Parameters ◽  
Moment Invariant ◽  
Plant Leaf ◽  
The Neural Networks ◽  
Novel Method ◽  
The Moment

This paper proposed a novel method for leaf classification and recognition. In the method, the moment invariant and fractal dimension were regarded as the characteristic parameters of the plant leaf. In order to extract the representative characteristic parameters, pretreatment of the leaf images, including RGB-gray converting, image binarization and leafstalk removing. The extracted leaf characteristic parameters were further utilized as training sets to train the neural networks. The proposed method was proved effectively to reach a recognition rate about 92% for most of the testing leaf samples

A novel method for the design and selection of neutron-attenuating media

2021 ◽  
Vol 160 ◽  
pp. 108368
Author(s):  
Abdullah G. Weiss ◽  
Moiz I. Butt ◽  
Pavel V. Tsvetkov ◽  
Mark L. Kimber ◽  
Sean M. McDeavitt
Keyword(s):  
Novel Method ◽  
Selection Of

scholarly journals Tuning of a Linear-Quadratic Stabilization System for an Anti-Aircraft Missile

Aerospace ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 48
Author(s):  
Witold Bużantowicz
Keyword(s):  
Analytical Solutions ◽  
Feedback Loop ◽  
Linear Quadratic Regulator ◽  
Added Value ◽  
Tuning Parameter ◽  
Stabilization System ◽  
Linear Quadratic ◽  
Quadratic Stabilization ◽  
Novel Method ◽  
Selection Of

A description is given of an application of a linear-quadratic regulator (LQR) for stabilizing the characteristics of an anti-aircraft missile, and an analytical method of selecting the weighting elements of the gain matrix in feedback loop is proposed. A novel method of LQR tuning via a single parameter ς was proposed and tested. The article supplements and develops the topics addressed in the author’s previous work. Its added value includes the observation that the solutions obtained are symmetric pairs, and that the tuning parameter ς proposed for the designed linear-quadratic regulator enables the selection of suitable parameters for the airframe stabilizing loop for the majority of the analytical solutions of the considered Riccati equation.

scholarly journals Cinnabar, Calomel and the Art of kushtasāzī: Mercurial Preparations in Unani Medicine

2015 ◽  
Vol 69 (4) ◽  
pp. 901-932 ◽  
Author(s):  
Claudia Preckel
Keyword(s):  
South Asia ◽  
Fifteenth Century ◽  
Medical Literature ◽  
Ancient Greece ◽  
Unani Medicine ◽  
Islamic Medicine ◽  
Selection Of

Abstract This paper examines the role of mercury in “Graeco-Islamic” medicine, which is referred to as Ṭibb-e yūnānī or unani medicine in South Asia. Having its origin in Ancient Greece, unani medicine spread to the Arabic countries and from the fifteenth century onwards to India. With its main roots in the Greek and Latin sources, the most influential works of ‘ilm al-adviya (pharmacology) were translated into Arabic, Persian and Urdu. Mercury (Arabic: zībaq; Persian: sīmāb; Urdu: sīmāb and pāra) played an important role in all Indian traditions of medicine, and had a prominent place in unani medicine. This paper highlights the historical use of mercury in Indian, Persian and Urdu medical literature, the discourses on its efficacy and some of the important mercurial preparations presented in a selection of unani works. Further, the use of mercury as a single and compound drug and its role in the treatment of different diseases will be analysed.

A novel method for predicting variant selection of {101¯2} twins in pure hafnium

2021 ◽  
pp. 130738
Author(s):  
Yingdong Zhang ◽  
Geping Li ◽  
Fusen Yuan ◽  
Fuzhou Han ◽  
Muhammad Ali ◽  
...  
Keyword(s):  
Variant Selection ◽  
Novel Method ◽  
Selection Of

scholarly journals Optimum Selection of Wind Turbines Using Normalized Power and Capacity Factor Curves

2021 ◽  
pp. 2813-2823
Author(s):  
Firas A. Hadi ◽  
Zaid F. Makki ◽  
Rafa A. Al-Baldawi
Keyword(s):  
Wind Turbine ◽  
Performance Index ◽  
Shape Parameter ◽  
Parameters Estimation ◽  
Capacity Factor ◽  
Turbine Performance ◽  
Optimum Selection ◽  
Novel Method ◽  
A Site ◽  
Selection Of

The main objective of this paper is present a novel method to choice a certain wind turbine for a specific site by using normalized power and capacity factor curves. The site matching is based on identifying the optimum turbine rotation speed parameters from turbine performance index (TPI) curve, which is obtained from the higher values of normalized power and capacity factor curves. Wind Turbine Performance Index a new ranking parameter, is defined to optimally match turbines to wind site. The relations (plots) of normalized power, capacity factor, and turbine performance index versus normalized rated wind speed are drawn for a known value of Weibull shape parameter of a site, thus a superior method is used for Weibull parameters estimation which is called Equivalent Energy Method (EEM).

scholarly journals Layer contour characterization in additive manufacturing through image binarization

2021 ◽  
Vol 1193 (1) ◽  
pp. 012067
Author(s):  
D Blanco ◽  
A Fernández ◽  
P Fernández ◽  
B J Álvarez ◽  
F Peña
Keyword(s):  
Digital Images ◽  
Median Filter ◽  
Threshold Value ◽  
Image Binarization ◽  
Actual Contour ◽  
Filter Size ◽  
Characterization Procedure ◽  
Flat Bed Scanner ◽  
Selection Of ◽  
Excellent Coverage

Abstract On-Machine Measurement adoption will be key to dimensional and geometrical improvement of additively manufactured parts. One possible approach based on OMM aims at using digital images of manufactured layers to characterize actual contour deviations with respect to their theoretical profile. This strategy would also allow for in-process corrective actions. This work describes a layer-contour characterization procedure based on binarization of digital images acquired with a flat-bed scanner. This procedure has been tested off-line to evaluate the influence of two of the parameters for image treatment, the median filter size (S f ) and the threshold value (T), on the dimensional/geometrical reliability of the contour characterization. Results showed that an appropriate selection of configuration parameters allowed to characterize the proposed test-target with excellent coverage and reasonable accuracy.

scholarly journals Infer disease-associated microbial biomarkers based on metagenomic and metatranscriptomic data

2021 ◽  
Author(s):  
Zhaoqian Liu ◽  
Qi Wang ◽  
Dongjun Chung ◽  
Qin Ma ◽  
Jing Zhao ◽  
...  
Keyword(s):  
Low Rank ◽  
Connected Components ◽  
Biomarker Identification ◽  
Gene Expression Matrix ◽  
Large Size ◽  
Microbial Biomarkers ◽  
Key Species ◽  
Novel Method ◽  
Inflammatory Bowel ◽  
Disease Subtypes

AbstractUnveiling disease-associated microbial biomarkers (e.g., key species, genes, and pathways) is an efficient strategy for the diagnosis and therapy of diseases. However, the heterogeneity and large size of microbial data bring tremendous challenges for fundamental characteristics discovery. We present IDAM, a novel method for disease-associated biomarker identification from metagenomic and metatranscriptomic data, without requiring prior metadata. It integrates gene context conservation and regulatory mechanism through a mathematical model for maximizing the number of connected components between local-low rank submatrices of a gene expression matrix and known uber-operon structures. We applied IDAM to 813 inflammatory bowel disease-associated datasets and showed IDAM outperformed existing methods in microbial biomarker identification. In addition, the identified biomarkers successfully distinguished disease subtypes and showcased their power in discovering novel disease subtypes/states. IDAM is freely available at https://github.com/OSU-BMBL/IDAM.

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