scholarly journals APPLYING IMAGE PROCESSING TOOLS TO ANALYZE THE SURFACE CHARACTERISTICS OF NANO ALUMINA (NANOAL2O3) AND NANO TITANIUM (NANOTIO2)

2018 ◽  
Vol 80 (4) ◽  
Author(s):  
Abdul-Adheem Zaily Hameed ◽  
Muzhir Shaban Al-Ani ◽  
Faik Hammad Anter
Keyword(s):  
Image Processing ◽  
Composite Material ◽  
Texture Analysis ◽  
Surface Texture ◽  
Quantitative Description ◽  
Surface Characteristics ◽  
Material Surface ◽  
Mean Values ◽  
Gray Image ◽  
Nano Alumina

Composite material is a material constructed of two or more materials that leads with different physical or chemical characteristics. Nano Alumina (NANO AL2O3) and Nano Titanium (NANO TIO2) are normally used to construct the composite material. The fundamental of texture analysis seeks to derive a general efficient and compact quantitative description of textures so that various mathematical operations can be used to achieve, compare and transform of texture characteristics. Many mechanical and physical methods are used to measure the surface characteristics. Some of these methods suffered from accurate description of material surface. In addition, the details of material surface are not clear via applying the traditional methods for surface analyzing. This work is concentrated on combining many functions and steps of image processing method to understand and analyze the surface characteristics of the composite material (Nano Alumina and Nano Titanium). The implemented approach including many steps: image enhancement, texture analysis, edge detection and contour analysis. This approach leads to explain, extract, analyze and evaluate the characteristics of surface texture of the composite material via measuring of mean values for original gray image, adjusted gray image, equalized gray image and adapted gray image. The average mean values of Nano Alumina are 103, 110, 128 and 134 for the applied method respectively. The average mean values of Nano titanium are 120, 123, 125 and 129 respectively. As a conclusion the implemented approach of surface texture analysis indicated that there is a significant improvement at the surface characteristics for both equalization and adaptive methods compared with the adjustment method.

Atomic structure of interface of intermetallic compound TiAl and nitride Ti2AIN using HREM and image processing

1991 ◽  
Vol 49 ◽  
pp. 570-571
Author(s):  
E. Sukedai ◽  
H. Mabuchi ◽  
H. Hashimoto ◽  
Y. Nakayama
Keyword(s):  
Mechanical Properties ◽  
Image Processing ◽  
Composite Material ◽  
Intermetallic Compound ◽  
Side Surface ◽  
High Resolution Electron Microscopy ◽  
Hexagonal Structure ◽  
Second Phase ◽  
Resolution Electron ◽  
Compound Tial

In order to improve the mechanical properties of an intermetal1ic compound TiAl, a composite material of TiAl involving a second phase Ti2AIN was prepared by a new combustion reaction method. It is found that Ti2AIN (hexagonal structure) is a rod shape as shown in Fig.1 and its side surface is almost parallel to the basal plane, and this composite material has distinguished strength at elevated temperature and considerable toughness at room temperature comparing with TiAl single phase material. Since the property of the interface of composite materials has strong influences to their mechanical properties, the structure of the interface of intermetallic compound and nitride on the areas corresponding to 2, 3 and 4 as shown in Fig.1 was investigated using high resolution electron microscopy and image processing.

scholarly journals Titanium oral implants: surface characteristics, interface biology and clinical outcome

2010 ◽  
Vol 7 (suppl_5) ◽  
Author(s):  
Anders Palmquist ◽  
Omar M. Omar ◽  
Marco Esposito ◽  
Jukka Lausmaa ◽  
Peter Thomsen
Keyword(s):  
Surface Properties ◽  
Cellular Response ◽  
Randomized Clinical Trials ◽  
Three Dimensional ◽  
Cell Communication ◽  
Surface Characteristics ◽  
Titanium Implants ◽  
Material Surface ◽  
Oral Implants

Bone-anchored titanium implants have revolutionized oral healthcare. Surface properties of oral titanium implants play decisive roles for molecular interactions, cellular response and bone regeneration. Nevertheless, the role of specific surface properties, such as chemical and phase composition and nanoscale features, for the biological in vivo performance remains to be established. Partly, this is due to limited transfer of state-of-the-art preparation techniques to complex three-dimensional geometries, analytical tools and access to minute, intact interfacial layers. As judged by the available results of a few randomized clinical trials, there is no evidence that any particular type of oral implant has superior long-term success. Important insights into the recruitment of mesenchymal stem cells, cell–cell communication at the interface and high-resolution imaging of the interface between the surface oxide and the biological host are prerequisites for the understanding of the mechanisms of osseointegration. Strategies for development of the next generation of material surface modifications for compromised tissue are likely to include time and functionally programmed properties, pharmacological modulation and incorporation of cellular components.

AN AUTOREGRESSIVE APPROACH TO SURFACE TEXTURE ANALYSIS

1994 ◽  
Vol 08 (04) ◽  
pp. 845-857 ◽  
Author(s):  
DINESH P. MITAL ◽  
GOH WEE LENG
Keyword(s):  
Aspect Ratio ◽  
Random Field ◽  
Texture Analysis ◽  
Surface Texture ◽  
Field Model ◽  
Invariant Property ◽  
Circular Area ◽  
Pixel Image ◽  
Rotational Invariant ◽  
Surface Texture Analysis

The use of autoregressive models in textual analysis holds great potential. Coupling the technique to a circular neighbourhood set imparts a rotational invariant property to it. This was demonstrated by Kashyap and Khotanzad in their model called the Circular Symmetric Autogressive (CSAR) Random Field model. The short-coming in this very ingenious proposal is that it is set in a background of square pixels and the rotational invariant property of the model fails in cases when the aspect ratio of the pixels are not at unity. This paper proposes a major modification to the CSAR to render the model rotational invariant under all configurations of pixel implementation. It is based on the area segments covered by a circle set in a 3×3 neighbourhood. We call it the Circular Area Autoregressive (CAAR) model. The results obtained from the CAAR showed much better consistency over that of the CSAR when a non-square pixel image was used.

scholarly journals A systematic assessment of water vapor products in the Arctic: from instantaneous measurements to monthly means

2021 ◽  
Vol 14 (7) ◽  
pp. 4829-4856
Author(s):  
Susanne Crewell ◽  
Kerstin Ebell ◽  
Patrick Konjari ◽  
Mario Mech ◽  
Tatiana Nomokonova ◽  
...  
Keyword(s):  
Water Vapor ◽  
Surface Characterization ◽  
Surface Characteristics ◽  
The Arctic ◽  
Monthly Means ◽  
Atlantic Sector ◽  
Mean Values ◽  
Systematic Assessment ◽  
Retrieval Algorithms ◽  
Spatio Temporal

Abstract. Water vapor is an important component in the water and energy cycle of the Arctic. Especially in light of Arctic amplification, changes in water vapor are of high interest but are difficult to observe due to the data sparsity of the region. The ACLOUD/PASCAL campaigns performed in May/June 2017 in the Arctic North Atlantic sector offers the opportunity to investigate the quality of various satellite and reanalysis products. Compared to reference measurements at R/V Polarstern frozen into the ice (around 82∘ N, 10∘ E) and at Ny-Ålesund, the integrated water vapor (IWV) from Infrared Atmospheric Sounding Interferometer (IASI) L2PPFv6 shows the best performance among all satellite products. Using all radiosonde stations within the region indicates some differences that might relate to different radiosonde types used. Atmospheric river events can cause rapid IWV changes by more than a factor of 2 in the Arctic. Despite the relatively dense sampling by polar-orbiting satellites, daily means can deviate by up to 50 % due to strong spatio-temporal IWV variability. For monthly mean values, this weather-induced variability cancels out, but systematic differences dominate, which particularly appear over different surface types, e.g., ocean and sea ice. In the data-sparse central Arctic north of 84∘ N, strong differences of 30 % in IWV monthly means between satellite products occur in the month of June, which likely result from the difficulties in considering the complex and changing surface characteristics of the melting ice within the retrieval algorithms. There is hope that the detailed surface characterization performed as part of the recently finished Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) will foster the improvement of future retrieval algorithms.

Brain Tumour Texture Analysis-A Method

2021 ◽  
Vol 4 (4) ◽  
Author(s):  
Samir Kumar Bandyopadhyay
Keyword(s):  
Image Processing ◽  
Brain Tumor ◽  
Texture Analysis ◽  
Brain Tumour ◽  
Tumor Segmentation ◽  
Biomedical Image Processing ◽  
Biomedical Analysis ◽  
Brain Tumor Segmentation ◽  
Human Brain Tumor ◽  
Biomedical Image

Computer aided technology is used in biomedical image processing. In biomedical analysis features are extracted and then the proposed method will detect any abnormalities present or not in the system to be considered. In recent days the detection of brain tumour through image processing is made in medical diagnosis. The separation of tumor is made by the process of segmentation. Brain in human is the most complicated and delicate anatomical structure. There are various brain ailments in human but the indication of cancer in brain tumour may be fatal for the human. Brain tumor can be malignant or benign. The neurologist or neurosurgeon wants to know the exact location, size, shape and texture of tumor from Magnetic Resonance Imaging (MRI) of brain before going to the operation of the brain tumour or decided whether operation of removing brain tumour is at all necessary or not. The disease is analyzed since operation may cause death to the patient. Initially they took a chance by prescribing medicines to see whether there is any improvement of the condition of the patient. If the result is not satisfactory then there is no option other than operation of the tumor. Doctors also take an attempt to find the texture of the tumor since it may help them to know the progress of the tumour. In addition to Brain tumor segmentation, the detection of surface of the texture of brain tumor is required for proper treatment. The chapter proposed methods for detection of the progressive nature of the texture in the tumor presence in brain. For this process segmentation of tumor from other parts of brain is essential. In the chapter segmentation techniques are presented before the texture analysis process is given. Finally, comparisons of the proposed method with other methods are analyzed.

Experimental Study on the Effect of Surface Integrity on Fatigue Performance of Aero-Engine Blades

2021 ◽  
Author(s):  
Yun Huang ◽  
Shaochuan Li ◽  
Guijian Xiao ◽  
Benqiang Chen ◽  
Yi He ◽  
...  
Keyword(s):  
Residual Stress ◽  
Surface Roughness ◽  
Fatigue Life ◽  
Fatigue Strength ◽  
Fatigue Test ◽  
Surface Texture ◽  
Surface Characteristics ◽  
Service Performance ◽  
Aero Engine ◽  
Vibration Fatigue

Abstract As the core component of aero-engine, the service performance of aero-engine blade has an important influence on the engine’s reliability and safety performance. Existing studies have shown that machined surface characteristics affect the fatigue strength of components. However, current studies are all based on regular fatigue samples. The structure of blades different from fatigue samples, and the influence mechanism of structural differences on the service performance of blades is still unclear. In addition, the conventional fatigue test conditions are not representative for the blades’ actual service conditions, so it is difficult to realize the processing process for the service performance optimization. In this study, the aero-engine blades processed by abrasive belt grinding and the vibration fatigue test bench were used to explore the influence of surface roughness, surface texture, and surface residual stress on the fatigue performance of aero-engine blades under actual working conditions. The aero-engine blades were ground with different process parameters to obtain different single-factor surface characteristics. By comparing the vibration fatigue life of blades with different surface features, the influence degree of each surface feature on the fatigue life was explored. Results showed that surface roughness has the greatest influence on fatigue strength, followed by residual stress, and surface texture has the least influence on fatigue strength.

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