scholarly journals Experimental Research on Internal Behaviors of Caved Rocks under the Uniaxial Confined Compression

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Yu-jiang Zhang ◽  
Guo-rui Feng ◽  
Ting-ye Qi
Keyword(s):  
Image Processing ◽  
Boundary Effect ◽  
Confined Compression ◽  
Compression Process ◽  
Strata Control ◽  
Processing Technologies ◽  
Experiment System ◽  
Two Stages ◽  
Density Boundary ◽  
Breakage Behavior

As main composition of longwall gob, caved rocks’ behaviors and their impacts under compression crucially influence strata control, subsidence, associated resources extraction, and many other aspects. However, current researches are based on a whole sample, due to looseness of caved rocks and limitation of observation technology. In this paper, an experiment system was built to investigate internal behaviors of caved rocks’ sample, under the uniaxial confined compression, including movement and breakage behavior by the digital image processing technologies. The results show that the compression process of caved rocks could be divided into two stages by relative density. Boundary effect and changes of voids and contact pressure among caved rocks lead to different movement law in different position in sample’s interior. A stratification phenomenon of breakage was discovered, which presents breakage concentration in the middle of the sample. The nonlinear movement and shear dislocation induced by shifts among caved rocks are the reason of the breakage stratification phenomenon. This phenomenon would have an effect on the permeability and seepage research of similar medium.

A Hair Volume Analysis System Using Deep Learning and Image Processing Technologies

2021 ◽  
Author(s):  
Ming-Che Chen ◽  
Wan-Jung Chang ◽  
Yu-Xiang Xiao ◽  
Zi-Xuan Zhang ◽  
Yi-Chan Chiu ◽  
...  
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Processing Technologies ◽  
Volume Analysis ◽  
Analysis System

scholarly journals PENERAPAN CITRA TERKOMPRESI PADA SEGMENTASI CITRA MENGGUNAKAN ALGORITMA K-MEANS

2018 ◽  
Vol 2 (1) ◽  
pp. 65-74
Author(s):  
Angga Wijaya Kusuma ◽  
Rossy Lydia Ellyana
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Medical Image ◽  
Performance Test ◽  
Input Image ◽  
Magnetic Resonance Imaging Image ◽  
Resonance Imaging ◽  
Compression Process ◽  
Mri Brain ◽  
Mri Image

In the development of an image not only as a documentation of events. One area that requires image processing is in the field of medicine is radiology. In radiology there is a medical image required by doctors and researchers to be processed for patient analysis. One of the important problems in image processing and pattern recognition is image segmentation into homogeneous areas. Segmentation in medical images will result in a medical image with area boundaries that are important information for analysis. This research applies k-means algorithm to MRI (Magnetic Resonance Imaging) image segmentation. The input image used is the image of MRI (brain and breast) has gone through the compression stage. This compression process is done with the aim of reducing memory usage but the critical information content of MRI image is still maintained. The image of the segmentation result is evaluated through performance test using GCE, VOI, MSE, and PSNR parameters.

Study on Soil Particle Size Distribution by Digital Image Processing

2013 ◽  
Vol 788 ◽  
pp. 627-630
Author(s):  
Jian Shu Hou
Keyword(s):  
Mechanical Property ◽  
Image Processing ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Digital Image ◽  
Traditional Method ◽  
Processing Method ◽  
Distribution Analysis ◽  
Processing Technologies

The particle size distribution of soil is very importantto its physical and mechanical property. The ordinary method of the particlesize distribution analysis is based on shaking the soil through a set of sieves.But it will be difficult to use the method while there have particles largerthan the biggest aperture of the size sieves. Then the digital image processingwas used to solve the problem here. The processing technologies, such as imageanalysis and enhancement, deblurring, edge detection were studied to analyzethe image of soil particles. Then the image processing method was used to getthe particle size distribution accurately. Though some promotions need to becarried out in the further study, it is can be found that the image processingmethod is more efficiently than the traditional method.

Application of the Quantitative Monochrome Calibrated Schlieren Technique in a Highly Loaded Turbine Cascade Test

2019 ◽  
Vol 141 (11) ◽  
Author(s):  
Zhihong Zhou ◽  
Haotian Wang ◽  
Huoxing Liu
Keyword(s):  
Shock Wave ◽  
Image Processing ◽  
Boundary Condition ◽  
Density Field ◽  
Dominant Factor ◽  
Turbine Cascade ◽  
Schlieren Technique ◽  
Computer Image Processing ◽  
Density Boundary ◽  
Highly Loaded

Abstract As the load of the turbine components of aircraft engines continuously increases, shock loss becomes the dominant factor of turbine stage loss and has become a hot topic. The Schlieren technique is one of the few effective experimental methods to observe and study shock wave and, thus, has been widely used. Nevertheless, limited by camera accuracy and computer image processing technology, quantitative schlieren analysis methods were difficult to achieve in engineering applications. Fortunately, several quantitative schlieren methods have been developed with the help of new digital technology. Applying the schlieren technique to the highly loaded turbine cascade test is of great significance to the study of shock wave in highly loaded turbine cascades. In this paper, the results of the quantitative density field and shock intensity and loss in the cascade are obtained by using a double-reflection-type monochrome schlieren device. The boundary condition of the density field is obtained by pressure test, and matlab software is used as image processing calculation tool. The quantitative results of this paper prove the feasibility of applying quantitative schlieren method to highly loaded turbine cascade tests. Also, the implemented image processing method and density boundary condition acquisition method are suitable and convenient for cascade flow and shock measurement tests.

Application of Quantitative Monochrome Calibrated Schlieren Technique in Highly-Loaded Turbine Cascade Test

2019 ◽  
Author(s):  
Zhihong Zhou ◽  
Haotian Wang ◽  
Huoxing Liu
Keyword(s):  
Shock Wave ◽  
Image Processing ◽  
Boundary Condition ◽  
Density Field ◽  
Dominant Factor ◽  
Turbine Cascade ◽  
Schlieren Technique ◽  
Computer Image Processing ◽  
Density Boundary ◽  
Highly Loaded

Abstract As the load of the turbine components of aircraft engines continuously increases, shock loss becomes the dominant factor of turbine stage loss and has become a hot topic. Schlieren technique is one of the few effective experimental methods to observe and study shock wave and, thus, has been widely used. Nevertheless, limited by camera accuracy and computer image processing technology, quantitative schlieren analysis methods were difficult to achieve in engineering applications. Fortunately, several quantitative schlieren methods have been developed with the help of new digital technology. Applying schlieren technique to the highly-loaded turbine cascade test is of great significance to the study of shock wave in highly-loaded turbine cascades. In this paper, the results of quantitative density field and shock intensity and loss in the cascade are obtained by using a double reflection type monochrome schlieren device. The boundary condition of density field is obtained by pressure test, and MATLAB software is used as image processing calculation tool. The quantitative results of this paper prove the feasibility of applying quantitative schlieren method to highly-loaded turbine cascade tests. Also, the implemented image processing method and density boundary condition acquisition method are suitable and convenient for cascade flow and shock measurement tests.

scholarly journals Development and Application of a Human–Machine Interface Using Head Control and Flexible Numeric Tables for the Severely Disabled

2020 ◽  
Vol 10 (19) ◽  
pp. 7005
Author(s):  
Che-Ming Chang ◽  
Chern-Sheng Lin ◽  
Wei-Cheng Chen ◽  
Chung-Ting Chen ◽  
Yu-Liang Hsu
Keyword(s):  
Image Processing ◽  
Skin Color ◽  
Digital Camera ◽  
Human Machine Interface ◽  
Head Motion ◽  
Processing Technologies ◽  
Color Recognition ◽  
Machine Interface ◽  
Head Control ◽  
Head Gestures

The human–machine interface with head control can be applied in many domains. This technology has the valuable application of helping people who cannot use their hands, enabling them to use a computer or speak. This study combines several image processing and computer vision technologies, a digital camera, and software to develop the following system: image processing technologies are adopted to capture the features of head motion; the recognized head gestures include forward, upward, downward, leftward, rightward, right-upper, right-lower, left-upper, and left-lower; corresponding sound modules are used so that patients can communicate with others through a phonetic system and numeric tables. Innovative skin color recognition technology can obtain head features in images. The barycenter of pixels in the feature area is then quickly calculated, and the offset of the barycenter is observed to judge the direction of head motion. This architecture can substantially reduce the distraction of non-targeted objects and enhance the accuracy of systematic judgment.

AUTOMATED CLASSIFICATION OF BREAST CARCINOMA CELL BASED ON IMAGE PROCESSING AND SUPPORT VECTOR MACHINE

2010 ◽  
Vol 22 (02) ◽  
pp. 127-135 ◽  
Author(s):  
Yung-Lung Kuo ◽  
Chien-Chuan Ko ◽  
Yueh-Min Lin ◽  
Yong-Min Chen
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Breast Cancer Diagnosis ◽  
Support Vector ◽  
Automated Classification ◽  
Processing Technologies ◽  
Major Health ◽  
Suitable Treatment ◽  
Breast Tissues

As breast cancer is a substantial threat to the lives of women, it has become a major health issue in the world over the past 50 years, and its incidence has increased in the recent years. Early diagnosis and suitable treatment is relatively important. In the process of breast screening, tissue biopsy is an important operation in determining the presence of breast cancer. It not only provides an accurate diagnosis of the disease but also determines the prognosis for breast cancer. The main goal of this study is to develop a breast cancer diagnosis system based on histopathology and a sequence of image-processing technologies to analyze H&E stained images of breast tissues. The proposed system can automatically detect the mitosis of nuclei and analyze the size and the shape of nuclei to evaluate the duct structure of the breast tissue. Moreover, it provides physicians quantitative prognosis and classification of tissue malignancy, which will improve the diagnostic accuracy and efficiency of the cancer.

Sign in / Sign up

Export Citation Format

Share Document