Quantification Evaluation of Continuous Fiber Composite Microstructure with Assistance of Image Processing Technique

2012 ◽  
Vol 622-623 ◽  
pp. 743-746
Author(s):  
Jiang Sun ◽  
Qi Xiao
Keyword(s):  
Image Processing ◽  
Fiber Composite ◽  
Processing Technique ◽  
Intensity Function ◽  
Second Order ◽  
Image Processing Technique ◽  
Two Phase ◽  
Structural Morphology ◽  
Composite Microstructure ◽  
Processing Techniques

The paper first introduced the method of analyzing the micro-structural morphology, then with assistance of image processing techniques and a second-order intensity function, simulated the two-phase composite micro-structure and selected its RVE. By an object function based on the second-order intensity function and using genetic algorithm, the RVE of original composite microstructure was created and its elastic moduli were analyzed. Numerical calculations showed that the represent volume element can well represent the original composite microstructure.

MATLAB Image Processing as a Viable Tool to Study Low Surface Roughness

2015 ◽  
Author(s):  
Wesley S. Hunko ◽  
Vishnuvardhan Chandrasekaran ◽  
Lewis N. Payton
Keyword(s):  
Image Processing ◽  
Surface Roughness ◽  
Standard Deviation ◽  
Data Acquisition ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Polished Surface ◽  
Digital Microscope ◽  
A New Technique ◽  
Processing Techniques

The purpose of this paper is to present the results of a study comparing an old technique for measuring low surface roughness with a new technique of data acquisition and processing that is potentially cheaper, quicker and more automated. It offers the promise of in-process quality monitoring of surface finish. Since the late 1800s, researchers have investigated the light scattering effects of surface asperities and have developed many interferometry techniques to quantify this phenomenon. Through the use of interferometry, the surface roughness of objects can be very accurately measured and compared. Unlike contact measurement such as profilometers, interferometry is nonintrusive and can take surface measurements at very wide ranges of scale. The drawbacks to this method are the high costs and complexity of data acquisition and analysis equipment. This study attempts to eliminate these drawbacks by developing a single built-in MATLAB function, to simplify data analysis, and a very economically priced digital microscope (less than $200), for data acquisition. This is done by comparing the results of various polishing compounds on the basis of the polished surface results obtained from MATLAB’s IMHIST function to the results of stylus profilometry methods. The study with the MATLAB method is also to be compared to 3D microscopy with a Keyence microscope. With surface roughness being a key component in many manufacturing and tribology applications, the apparent need for accurate, reliable and economical measuring systems is prevalent. However, interferometry is not a cheap or simple process. “Over the last few years, advances in image processing techniques have provided a basis for developing image-based surface roughness measuring techniques” [1]. One popular image processing technique is through the use of MATLAB’s Image Processing Toolbox. This includes an array of functions that can be used to quantify and compare textures of a surface. Some of these include standard deviation, entropy, and histograms of images for further analysis. “These statistics can characterize the texture of an image because they provide information about the local variability of the intensity values of pixels in an image. For example, in areas with smooth texture, the range of values in the neighborhood around a pixel will be a small value; in areas of rough texture, the range will be larger. Similarly, calculating the standard deviation of pixels in a neighborhood can indicate the degree of variability of pixel values in that region” [2]. By combining the practices of interferometry with the processing techniques of MATLAB, this fairly new method of roughness measurement proved itself as a very viable and inexpensive technique. This technique should prove to be a very viable means of interferometry at an affordable cost.

Computational Estimation of Bubble Gas Velocity for Slug Flow Pattern in Horizontal Pipes Using Image Processing Technique

2012 ◽  
Author(s):  
María T. Valecillos ◽  
Carlos H. Romero ◽  
María A. Márquez ◽  
Sissi D. Vergara
Keyword(s):  
Image Processing ◽  
Flow Pattern ◽  
Slug Flow ◽  
High Speed ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Gas Velocity ◽  
Two Phase ◽  
Horizontal Pipes ◽  
Computational Estimation

Two-phase slug flow pattern is one of the most common flow patterns present in many industries, therefore its study becomes relevant. The aim of this work was to develop an automated computational program to determine the bubble gas velocity associated to gas-liquid two-phase slug flow by using video digital image processing technique. In order to obtain the images for the analysis, experiments were carried out using a pipe bench for air-water two-phase flow. The experimental facility is located in Simon Bolivar University, in Venezuela. The system has three pipes with different internal diameters and can be rotated around its axis and fixed at any inclination angle from horizontal to vertical flow. The tests were run in a horizontal pipeline of 0.03175m of internal pipe diameter and 8m long. For slug flow visualization a high speed camera Kodak Ektapro 4540mx imager was used. The camera was located in an x/D relation corresponding to 249 from the pipe inlet, ensuring the complete development of the flow. The camera allowed a maximum acquisition velocity of 4500 frames per second. The superficial velocity range was 0.16–1.79m/s and 0.16–1.26m/s for air and water, respectively. To summarize, 165 tests were performed and 1320000 images were analyzed with 20 flow rate combinations. The computational application was validated by comparing it with the velocities measured manually over selected images. Results obtained were compared to several correlations such as Bendiksen [1], Cook & Behnia [2] and Wang et al. [3].

scholarly journals Specifics of Using Image Processing Techniques for Blood Smear Analysis

2020 ◽  
Vol 1 (6) ◽  
pp. 1-6
Author(s):  
Vyacheslav Lyashenko ◽  
Tetiana Sinelnikova ◽  
Oleksandr Zeleniy ◽  
Asaad Mohammed Ahmed Babker
Keyword(s):  
Image Processing ◽  
Human Health ◽  
Medical Diagnosis ◽  
Blood Smear ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Image Processing Techniques ◽  
Important Stage ◽  
Blood Smears ◽  
Processing Techniques

The process of medical diagnosis is an important stage in the study of human health. One of the directions of such diagnostics is the analysis of images of blood smears. In doing so, it is important to use different methods and analysis tools for image processing. It is also important to consider the specificity of blood smear imaging. The paper discusses various methods for analyzing blood smear images. The features of the application of the image processing technique for the analysis of a blood smear are highlighted. The results of processing blood smear images are presented.

scholarly journals Improved Image Processing Techniques for User Immersion Problem Alleviation in Virtual Reality Environments

2020 ◽  
Vol 2 (2) ◽  
pp. 77-84
Author(s):  
Dr. Dhaya R.
Keyword(s):  
Image Processing ◽  
Virtual Reality ◽  
Processing Speed ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Image Processing Techniques ◽  
Processing Techniques

The latest advertisements on the advancements of the virtual reality has paved way for diverse studies, in manifold fields that can benefit by utilizing the technologies of the virtual reality, not excluding the design, gaming and the simulated understanding. Yet whenever a virtual reality device conveys information in form of images with the assistance of the display that is positioned closer to the user’s eyes it faces problems like minimizing the speed of the process and degradation in the quality of images ending up in huge variations across the virtual realism and the realism causing user immersion problems. So to mitigate the immersion problems of the user because of the low quality of image and the minimization of processing speed in the virtual reality environments the paper puts forth an improved image processing technique to improvise the sharpness of the images in order to enhance quality of the images and heighten the processing speed.

Image Processing Technique for the Detection of Alberseem Leaves Diseases Based on Soft Computing

2021 ◽  
pp. 103-115
Author(s):  
Eimad Abdu Abusham
Keyword(s):  
Image Processing ◽  
Traditional Method ◽  
Processing Technique ◽  
Plant Diseases ◽  
Image Processing Technique ◽  
Economic Losses ◽  
Image Processing Techniques ◽  
Appropriate Treatment ◽  
Processing Techniques

Detecting plant diseases using the traditional method such as the naked eye can sometimes lead to incorrect identification and classification of the diseases. Consequently, this traditional method can strongly contribute to the losses of the crop. Image processing techniques have been used as an approach to detect and classify plant diseases. This study aims to focus on the diseases affecting the leaves of al-berseem and how to use image processing techniques to detect al-berseem diseases. Early detection of diseases important for finding appropriate treatment quickly and avoid economic losses. Detect the plant disease is based on the symptoms and signs that appear on the leaves. The detection steps include image preprocessing, segmentation, and identification. The image noise is removed in the preprocessing stage by using the MATLAB features energy, mean, homogeneity, and others. The k-mean-clustering is used to detect the affected area in leaves. Finally, KNN will be used to recognize unhealthy leaves and determines disease types (fungal diseases, pest diseases (shall), leaf minor (red spider), and deficiency of nutrient (yellow leaf)); these four types of diseases will detect in this thesis. Identification is the last step in which the disease will identify and classified.

scholarly journals Repeatability of binarization thresholding methods for optical coherence tomography angiography image quantification

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Nihaal Mehta ◽  
Phillip X. Braun ◽  
Isaac Gendelman ◽  
A. Yasin Alibhai ◽  
Malvika Arya ◽  
...  
Keyword(s):  
Image Processing ◽  
Optical Coherence Tomography ◽  
Optical Coherence Tomography Angiography ◽  
Histogram Equalization ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Foveal Avascular Zone ◽  
Optical Coherence ◽  
Multiple Devices ◽  
Processing Techniques

Abstract Binarization is a critical step in analysis of retinal optical coherence tomography angiography (OCTA) images, but the repeatability of metrics produced from various binarization methods has not been fully assessed. This study set out to examine the repeatability of OCTA quantification metrics produced using different binarization thresholding methods, all of which have been applied in previous studies, across multiple devices and plexuses. Successive 3 × 3 mm foveal OCTA images of 13 healthy eyes were obtained on three different devices. For each image, contrast adjustments, 3 image processing techniques (linear registration, histogram normalization, and contrast-limited adaptive histogram equalization), and 11 binarization thresholding methods were independently applied. Vessel area density (VAD) and vessel length were calculated for retinal vascular images. Choriocapillaris (CC) images were quantified for VAD and flow deficit metrics. Repeatability, measured using the intra-class correlation coefficient, was inconsistent and generally not high (ICC < 0.8) across binarization thresholds, devices, and plexuses. In retinal vascular images, local thresholds tended to incorrectly binarize the foveal avascular zone as white (i.e., wrongly indicating flow). No image processing technique analyzed consistently resulted in highly repeatable metrics. Across contrast changes, retinal vascular images showed the lowest repeatability and CC images showed the highest.

scholarly journals Application of Neuro-Wavelet Algorithm in Ultrasonic-Phased Array Nondestructive Testing of Polyethylene Pipelines

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Reza Bohlouli ◽  
Babak Rostami ◽  
Jafar Keighobadi
Keyword(s):  
Image Processing ◽  
Nondestructive Testing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Phased Array ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Image Processing Techniques ◽  
Ultrasonic Phased Array ◽  
Processing Techniques

Polyethylene (PE) pipelines with electrofusion (EF) joining is an essential method of transportation of gas energy. EF joints are weak points for leakage and therefore, Nondestructive testing (NDT) methods including ultrasonic array technology are necessary. This paper presents a practical NDT method of fusion joints of polyethylene piping using intelligent ultrasonic image processing techniques. In the proposed method, to detect the defects of electrofusion joints, the NDT is applied based on an ANN-Wavelet method as a digital image processing technique. The proposed approach includes four steps. First an ultrasonic-phased array technique is used to provide real time images of high resolution. In the second step, the images are preprocessed by digital image processing techniques for noise reduction and detection of ROI (Region of Interest). Furthermore, to make more improvement on the images, mathematical morphology techniques such as dilation and erosion are applied. In the 3rd step, a wavelet transform is used to develop a feature vector containing 3-dimensional information on various types of defects. In the final step, all the feature vectors are classified through a backpropagation-based ANN algorithm. The obtained results show that the proposed algorithms are highly reliable and also precise for NDT monitoring.

scholarly journals A Soft Approach to Estimate Woody Volume of a Live Tree

2017 ◽  
Vol 10 (3) ◽  
pp. 618-623 ◽  
Author(s):  
NIKITA SINGLA ◽  
DERMINDER SINGH
Keyword(s):  
Image Processing ◽  
Processing Technique ◽  
Experimental Results ◽  
Image Processing Technique ◽  
Percentage Error ◽  
Standing Tree ◽  
Individual Tree ◽  
Live Tree ◽  
Processing Techniques ◽  
Areas Of Interest

Tree volume is one of the oldest areas of interest and is a crucial task in tree management system. Estimating the woody volume of a live tree is important for economic, scientific purposes and provides a tool to researcher/grower. It provides the useful information about the commercial value of wood to the potential buyer/seller. However, manual methods are being used largely to calculate woody volume of a tree. These methods are based on different log rules, cumbersome and laborious. The present work proposed a digital image processing technique to estimate the woody volume of a live tree. The developed program successfully determines the woody volume of standing tree trunk with MATLAB image processing techniques. In this method three parameters an individual tree were extracted from digital images of the tree. Calibration factor was also calculated to make the method independent of camera distance from the tree. The method was tested on several samples of trees and compared to experimental results. The soft approach generates information about height, diameter and volume of the tree. The percentage error of height, diameter at breast height and volume of standing tree by proposed method and experimental results was found to be less than 6.65%.

scholarly journals Diabetic Maculopathy Detection using Image Processing

2019 ◽  
Vol 9 (1S3) ◽  
pp. 115-119
Keyword(s):  
Image Processing ◽  
Diabetic Retinopathy ◽  
Continuous Monitoring ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Human Beings ◽  
Diabetic Maculopathy ◽  
Monitoring Process ◽  
Physical Tests ◽  
Processing Techniques

Diabetic Retinopathy (DR) is a serious eye disease caused to human beings having diabetics. DR will affect the retina of the eye and even it may lead to complete blindness. It is essential to have an early treatment for the diagnosis of DR to avoid blindness. There are many physical tests like visual test, pupil dilation to detect retinopathy but all are time consuming processes. For diabetic retinopathy, it needs a continuous monitoring process. The main objective of this work is to detect diabetic maculopathy which is one of the major retinal abnormalities found among diabetic persons. Diabetic maculopathy is detected using image processing technique. In image processing techniques, we use image pre processing to reduce the noise and use segmentation process to extract the features of the macula. After that the features are compared using the classifier algorithm and the performances are measured using the accuracy, sensitivity and specificity.

Sign in / Sign up

Export Citation Format

Share Document