Novel Approach for Surface Defect Analysis of Friction Stir Welded Lightweight Automotive Metal Alloys by using Local Binary Patterns

2020 ◽  
Vol 07 (1&2) ◽  
pp. 8-14
Author(s):  
Akshansh Mishra ◽  
Keyword(s):  
Surface Defect ◽  
Local Binary Patterns ◽  
Metal Alloys ◽  
Defect Analysis ◽  
Friction Stir ◽  
Novel Approach

A novel approach for producing polymer nanocomposites by in-situ dispersion of clay particles via friction stir processing

2011 ◽  
Vol 528 (6) ◽  
pp. 3003-3006 ◽  
Author(s):  
Mohsen Barmouz ◽  
Javad Seyfi ◽  
Mohammad Kazem Besharati Givi ◽  
Iman Hejazi ◽  
Seyed Mohammad Davachi
Keyword(s):  
Polymer Nanocomposites ◽  
Friction Stir Processing ◽  
Clay Particles ◽  
Friction Stir ◽  
Novel Approach

3D surface defect analysis and evaluation

2008 ◽  
Author(s):  
B. Yang ◽  
M. Jia ◽  
G. J. Song ◽  
L. Tao ◽  
K. G. Harding
Keyword(s):  
Surface Defect ◽  
Defect Analysis ◽  
Analysis And Evaluation ◽  
3D Surface

Volumetric defect analysis in friction stir welding based on three dimensional reconstructed images

2017 ◽  
Vol 29 ◽  
pp. 96-112 ◽  
Author(s):  
Chirag Parikh ◽  
Ravi Ranjan ◽  
Aaquib Reza Khan ◽  
Rahul Jain ◽  
Raju Prasad Mahto ◽  
...  
Keyword(s):  
Friction Stir Welding ◽  
Three Dimensional ◽  
Defect Analysis ◽  
Friction Stir

scholarly journals Generalized Completed Local Binary Patterns for Time-Efficient Steel Surface Defect Classification

2019 ◽  
Vol 68 (3) ◽  
pp. 667-679 ◽  
Author(s):  
Qiwu Luo ◽  
Yichuang Sun ◽  
Pengcheng Li ◽  
Oluyomi Simpson ◽  
Lu Tian ◽  
...  
Keyword(s):  
Steel Surface ◽  
Surface Defect ◽  
Local Binary Patterns ◽  
Defect Classification

A novel approach for producing in situ Al-Al2Cu composite via friction stir processing

2018 ◽  
Vol 6 (3) ◽  
pp. 036528 ◽  
Author(s):  
M Azizieh ◽  
M A G Dezfuli ◽  
Z Balak ◽  
H S Kim
Keyword(s):  
Friction Stir Processing ◽  
Friction Stir ◽  
Novel Approach

scholarly journals A Computer-Aided Detection System for Digital Chest Radiographs

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Juan Manuel Carrillo-de-Gea ◽  
Ginés García-Mateos ◽  
José Luis Fernández-Alemán ◽  
José Luis Hernández-Hernández
Keyword(s):  
Template Matching ◽  
Detection System ◽  
Local Binary Patterns ◽  
Chest Radiographs ◽  
Computer Aided Detection ◽  
Success Rates ◽  
Novel Approach ◽  
Computer Aided ◽  
Digital Chest ◽  
Areas Of Interest

Computer-aided detection systems aim at the automatic detection of diseases using different medical imaging modalities. In this paper, a novel approach to detecting normality/pathology in digital chest radiographs is proposed. The problem tackled is complicated since it is not focused on particular diseases but anything that differs from what is considered as normality. First, the areas of interest of the chest are found using template matching on the images. Then, a texture descriptor called local binary patterns (LBP) is computed for those areas. After that, LBP histograms are applied in a classifier algorithm, which produces the final normality/pathology decision. Our experimental results show the feasibility of the proposal, with success rates above 87% in the best cases. Moreover, our technique is able to locate the possible areas of pathology in nonnormal radiographs. Strengths and limitations of the proposed approach are described in the Conclusions.

Sign in / Sign up

Export Citation Format

Share Document