Research on Predicting Model of Surface Roughness for Ground Engineering Ceramics

2012 ◽  
Vol 476-478 ◽  
pp. 1036-1040
Author(s):  
Xin Li Tian ◽  
Jian Quan Wang ◽  
Bao Guo Zhang ◽  
Fu Qiang Li
Keyword(s):  
Ground Surface ◽  
Texture Features ◽  
Engineering Ceramics ◽  
Texture Parameters ◽  
Digital Microscope ◽  
Occurrence Matrix ◽  
The Relationship ◽  
Regression Theory ◽  
Surface Images

Grinding is the mostly leading machining technology for engineering ceramics. The quality of ground surface can be evaluated by various roughness parameters. And a textural analysis method based on Gray Level Co-occurrence Matrix was employed in researching the roughness of ground ceramics. The relationship between texture features and roughness was investigated through a series of surface images of engineering ceramics collected by a digital microscope. The sampling offset and total gray levels of surface images were determined firstly. Then 4 GLCMs were built up to calculate the average of texture features. And 6 parameters were fixed as main texture parameters. Furthermore, the multiple nonlinear regression theory was used to assess the relation between the texture features and roughness Ra. By statistic test and comparison, the deviation of calculated Ra and actual Ra is less than 0.25. It is shown that this relation is much satisfactory and the method may be suitable for quickly measuring the roughness of ground ceramics.

Study on the Relationship between Surface Roughness and Texture Features of Engineering Ceramics

2011 ◽  
Vol 697-698 ◽  
pp. 117-120
Author(s):  
Xin Li Tian ◽  
Jian Quan Wang ◽  
Fang Guo
Keyword(s):  
Surface Roughness ◽  
Texture Feature ◽  
Ground Surface ◽  
Texture Features ◽  
Key Factors ◽  
Machined Surface ◽  
Texture Parameters ◽  
Occurrence Matrix ◽  
The Relationship

The surface roughness and surface texture feature both are the key factors to evaluate the ground ceramics surface. The Gray Level Co-occurrence Matrix (GLCM) is introduced to extract and analyze the texture features of ground surface, in order to discover the relationship between texture features and roughness, and predict the roughness of ground ceramics according to the defined texture parameters. Four matrices about different sampling orientations are built up after the sampling offset and total gray levels are determined. By analyzing the correlation about every two features, Contrast, SS and ASM are selected to characterize the texture information of machined surface. Finally, the paper reveals the linear variation laws between Ra, Ry, S, tp and above features. The grounding quality of ceramic products also can be roughly estimated on the ground of that.

scholarly journals Texture Analysis of The Microstructure of Internal Curing Concrete Based On Image Recognition Technology

2021 ◽  
Author(s):  
Lixia Guo ◽  
Weikai Wang ◽  
Ling Zhong ◽  
Lei Guo ◽  
Fangfang Zhang ◽  
...  
Keyword(s):  
Compressive Strength ◽  
Image Recognition ◽  
Texture Features ◽  
Internal Curing ◽  
Effective Parameters ◽  
Texture Parameter ◽  
Texture Parameters ◽  
Occurrence Matrix ◽  
Cementing Material ◽  
The Relationship

Abstract Mechanical properties of internal curing concrete are greatly affected by its physical properties such as water content, cementing material content, porosity, and saturation. At the micro level, such impact is finally reflected in the surface texture of its materials. In this study, the image recognition technology was used to find that the internal curing concrete samples have significant micromorphology and texture features. A texture parameter–strength model was established based on the relationship between Tamura texture parameters, gray level co-occurrence matrix (GLCM) texture parameters, and the mechanical strength. Due to the characteristics of materials and the sensitivity of parameters, not all Tamura and GLCM texture parameters can effectively characterize the texture features of internal curing concrete materials. In terms of the Tamura texture, coarseness, regularity, and directionality are effective parameters to predict the compressive strength of the internal curing concrete. In terms of the GLCM texture, energy, correlation, entropy, and contrast are effective parameters to predict the compressive strength of the internal curing concrete. Correlations between each texture parameter and compressive strength follow different laws.

scholarly journals Automatic Classification for Fruits’ Types and Identification of Rotten Ones Using k-NN and SVM

2019 ◽  
Vol 15 (03) ◽  
pp. 47 ◽  
Author(s):  
Ann Nosseir ◽  
Seif Eldin A. Ahmed
Keyword(s):  
Texture Feature ◽  
Texture Features ◽  
Nearest Neighbors ◽  
Support Vector ◽  
K Nearest Neighbors ◽  
A Value ◽  
Different Types ◽  
Linear Svm ◽  
Occurrence Matrix

Having a system that classifies different types of fruits and identifies the quality of fruits will be of a value in various areas especially in an area of mass production of fruits’ products. This paper presents a novel system that differentiates between four fruits types and identifies the decayed ones from the fresh. The algorithms used are based on the colour and the texture features of the fruits’ images. The algorithms extract the RGB values and the first statistical order and second statistical of the Gray Level Co-occurrence Matrix (GLCM) values. To segregate between the fruits’ types, Fine, Medium, Coarse, Cosine, Cubic, and Weighted K-Nearest Neighbors algorithms are applied. The accuracy percentages of each are 96.3%, 93.8%, 25%, 83.8%, 90%, and 95% respectively.  These steps are tested with 46 pictures taken from a mobile phone of seasonal fruits at the time i.e., banana, apple, and strawberry. All types were accurately identifying.  To tell apart the decayed fruits from the fresh, the linear and quadratic Support Vector Machine (SVM) algorithms differentiated between them based on the colour segmentation and the texture feature algorithms values of each fruit image. The accuracy of the linear SVM is 96% and quadratic SVM 98%.

Experiment Research on Temperature Field in Ultrasonic Assisted Grinding Engineering Ceramics

2007 ◽  
Vol 364-366 ◽  
pp. 728-732 ◽  
Author(s):  
Guo Fu Gao ◽  
Chuan Shao Liu ◽  
Bo Zhao ◽  
Feng Jiao ◽  
Qing Hua Kong
Keyword(s):  
Surface Temperature ◽  
Ground Surface ◽  
Ceramic Materials ◽  
Grinding Wheel ◽  
Key Factors ◽  
Engineering Ceramics ◽  
Grinding Parameters ◽  
Orthogonal Experiments ◽  
Ultrasonic Assisted ◽  
The Relationship

As one of the key factors grinding heat has a significant effect on the ground surface quality in grinding engineering ceramics using diamond grinding wheel. Differences between mechanical and physical performances of ceramic materials and grinding parameters have important influences on the surface temperature distribution. In the present research, experiments with/without ultrasonic assistance were carried out to study the temperature characteristics in the grinding field by thermocouple in grinding ZrO2 and Al2O3 engineering ceramics respectively. Moreover, the theoretical analysis and the experiment confirmation for the relationship between grinding parameters and temperature have been discussed. The results show that the further the heat source keeps against grinding surface, the lower the peak value of temperature, and the surface temperature increases with the grinding depth, grinding speed and work table speed. According to the results of orthogonal experiments on grinding parameters, the grinding depth is the most important factor affecting the grinding temperature on the workpiece surface.

Monitoring Volcanic Activity of Baekdu Mountain based on Ice Area Changes During the Winters of 2015-2020

2021 ◽  
Author(s):  
Arip Syaripudin Nur ◽  
Sungjae Park ◽  
Seulki Lee ◽  
Chang-Wook Lee
Keyword(s):  
Vertical Transmission ◽  
Air Temperature ◽  
Volcanic Activity ◽  
Texture Features ◽  
Support Vector ◽  
Covered Area ◽  
Svm Algorithm ◽  
Highly Correlated ◽  
Occurrence Matrix ◽  
The Relationship

<p>Baekdu Mountain is a 2,744 m high stratovolcano, located on the border of China and North Korea. The mountain has a caldera lake, Lake Cheonji, as a result of past volcanic activity. The ice area changes during winter in Lake Cheonji could act as a proxy for volcanic activity monitoring in Baekdu. As Baekdu laid on a political border, remote sensing allows us to quantify attributes of otherwise inaccessible or dangerous places. We assessed changes in winter (October–April) ice area in a high-altitude groundwater-fed caldera lake using Sentinel-1 synthetic aperture radar (SAR) data acquired from 2015 to 2020. To calculate the ice-covered area, 10 gray level co-occurrence matrix (GLCM) texture features were computed from SAR images obtained with VH (vertical transmission and horizontal reception) and VV (vertical transmission and vertical reception) polarizations. A support vector machine (SVM) algorithm was used to classify ice and water pixels from the GLCM layers, and the results from VH and VV imagery were combined to calculate the total area covered by ice. We examined the relationship between ice area and air temperature from the closest weather station, Samjiyeon using fixed period regression. The ice area was inversely proportional to 30-day averaged air temperature and these variables were highly correlated (-0.86). Our results show that there were no significant ice changes during the period, which indicates that there was no significant volcanic activity in Baekdu Mountain during the winters of 2015–2020. This study is expected to be useful for a better understanding of whether and how ice area changes in volcano lakes aid in eruption forecasting.</p>

Analysis of Image Texture Features Based on Gray Level Co-Occurrence Matrix

2012 ◽  
Vol 204-208 ◽  
pp. 4746-4750 ◽  
Author(s):  
Ying Chen ◽  
Feng Yu Yang
Keyword(s):  
Quality Evaluation ◽  
Texture Features ◽  
Image Texture ◽  
Generation Process ◽  
Gray Level ◽  
Analysis Process ◽  
Comprehensive Information ◽  
Occurrence Matrix ◽  
The Relationship ◽  
Secondary Diagonal

Gray level co-occurrence matrix (GLCM) is a second-order statistical measure of image grayscale which reflects the comprehensive information of image grayscale in the direction, local neighborhood and magnitude of changes. Firstly, we analyze and reveal the generation process of gray level co-occurrence matrix from horizontal, vertical and principal and secondary diagonal directions. Secondly, we use Brodatz texture images as samples, and analyze the relationship between non-zero elements of gray level co-occurrence matrix in changes of both direction and distances of each pixels pair by. Finally, we explain its function of the analysis process of texture. This paper can provided certain referential significance in the application of using gray level co-occurrence matrix at quality evaluation of texture image.

Human Health Diagnosis System Based on Iris Features

2018 ◽  
pp. 905-928
Author(s):  
Poonguzhali N ◽  
M. Ezhilarasan ◽  
R. Hariharan ◽  
N. Praveen Devaraajan
Keyword(s):  
Human Health ◽  
Texture Features ◽  
High Accuracy ◽  
Health Condition ◽  
Statistical Measure ◽  
Human Iris ◽  
Authentication System ◽  
Real Time Applications ◽  
Occurrence Matrix ◽  
The Relationship

Iris feature has been used in authentication systems in many real time applications and is proved to provide high accuracy. Apart from authentication iris features can also be used for detecting pathological changes in human body and diagnose human health. The present study analyses the relationship between human iris anatomy and their health, as it is proved that changes in human health condition reflects the iris. Basically, in authentication system iris texture features are used for identification, in the proposed work iris texture and geometric features can also be deployed in diagnosing human health. The texture features present in the human iris are extracted using the mathematical statistical measure which is used to specify the characteristics of the texture of an image using gray-level co-occurrence matrix. The iris and pupil are extracted and correlated to the compactness features of the circle. Based on the comparison the system enables in prediction of abnormalities in the iris texture and identifies the affected person.

Human Health Diagnosis System Based on Iris Features

2017 ◽  
pp. 118-145
Author(s):  
Poonguzhali N ◽  
M. Ezhilarasan ◽  
R. Hariharan ◽  
N. Praveen Devaraajan
Keyword(s):  
Human Health ◽  
Texture Features ◽  
High Accuracy ◽  
Health Condition ◽  
Statistical Measure ◽  
Human Iris ◽  
Authentication System ◽  
Real Time Applications ◽  
Occurrence Matrix ◽  
The Relationship

Iris feature has been used in authentication systems in many real time applications and is proved to provide high accuracy. Apart from authentication iris features can also be used for detecting pathological changes in human body and diagnose human health. The present study analyses the relationship between human iris anatomy and their health, as it is proved that changes in human health condition reflects the iris. Basically, in authentication system iris texture features are used for identification, in the proposed work iris texture and geometric features can also be deployed in diagnosing human health. The texture features present in the human iris are extracted using the mathematical statistical measure which is used to specify the characteristics of the texture of an image using gray-level co-occurrence matrix. The iris and pupil are extracted and correlated to the compactness features of the circle. Based on the comparison the system enables in prediction of abnormalities in the iris texture and identifies the affected person.

Analysis of Micropattern Fabrication for Micromold Using Low Power CO2 Laser

2015 ◽  
Vol 758 ◽  
pp. 51-56
Author(s):  
Ario Sunar Baskoro ◽  
Yendri Minggu Bali
Keyword(s):  
Surface Roughness ◽  
Manufacturing System ◽  
Geometrical Properties ◽  
Dependent Variables ◽  
Digital Microscope ◽  
Research Experiment ◽  
Relationship Of ◽  
The Relationship ◽  
Microfabrication Techniques

The development of innovative micro components depends on the manufacturing system and process that reliable to produce the component in micro scale with good quality. In this case, using CO2Laser is one of microfabrication techniques to fabricate material to get micro component. In this research, experiment was performed to fabricate micropattern using engraving method by Laser CO2machine with several independent variables such as focus distance of nozzle Laser to workpiece (F), power of Laser (P), and velocity of nozzle Laser movement (V). The workpiece in this research was acrylic. Result of fabrication process will be identified and measured using digital microscope and surface roughness tester to get the value of workpiece quality such as surface roughness and geometrical properties as the dependent variables. The relationship of both variables will be expressed in 3D curves characteristic and mathematical models were analyzed by response surface methodology (RSM). The result of the analysis shows that the power of Laser (P) and velocity of Laser nozzle movement (V) effect is the significant variables affecting the quality of micropattern and micromold fabrications. Micromold can be fabricated using Laser CO2with roughness value (Rax) is 17,55μm, width of grove (W) is 135 μm, depth (D) is 341 μm.

scholarly journals Human Health Diagnosis System Based on Iris Features

Ophthalmology ◽  
2018 ◽  
pp. 217-240
Author(s):  
Poonguzhali N ◽  
M. Ezhilarasan ◽  
R. Hariharan ◽  
N. Praveen Devaraajan
Keyword(s):  
Human Health ◽  
Texture Features ◽  
High Accuracy ◽  
Health Condition ◽  
Statistical Measure ◽  
Human Iris ◽  
Authentication System ◽  
Real Time Applications ◽  
Occurrence Matrix ◽  
The Relationship

Iris feature has been used in authentication systems in many real time applications and is proved to provide high accuracy. Apart from authentication iris features can also be used for detecting pathological changes in human body and diagnose human health. The present study analyses the relationship between human iris anatomy and their health, as it is proved that changes in human health condition reflects the iris. Basically, in authentication system iris texture features are used for identification, in the proposed work iris texture and geometric features can also be deployed in diagnosing human health. The texture features present in the human iris are extracted using the mathematical statistical measure which is used to specify the characteristics of the texture of an image using gray-level co-occurrence matrix. The iris and pupil are extracted and correlated to the compactness features of the circle. Based on the comparison the system enables in prediction of abnormalities in the iris texture and identifies the affected person.

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