Improvements in Quality of Neutron Radiography Images of Pyro Components Used in Aerospace Applications Using Image Processing Tools

Author(s):  
Girish N. Namboodiri ◽  
V. Shaheer Ali ◽  
M. C. Santhosh Kumar ◽  
K. K. Moideenkutty ◽  
M. Nallaperumal ◽  
...  
2020 ◽  
Vol 10 (1) ◽  
pp. 11
Author(s):  
Ayu Fitri Amalia ◽  
Widodo Budhi

The digital image processing is one way to manipulate one or more digital images. Image segmentation has an essential role in the field of image analysis. The aim of this study was to develop an application to perform digital image processing of neutron digital radiographic images, hoping to improve the image quality of the digital images produced. The quality of edge detection could be used for the introduction of neutron digital radiographic image patterns through artificial intelligence. Interaction of neutrons with the matter mainly by nuclear reaction, elastic, and inelastic scattering. A neutron can quickly enter into a nucleus of an atom and cause a reaction. It is because a neutron has no charge. Neutrons can be used for digital imaging due to high-resolution information from deep layers of the material. The attenuated neutron beam in neutron radiography are passing through the investigated object. The object in a uniform neutron beam is irradiated to obtain an image neutron. The technique used in segmenting the neutron radiography in this study was a digital technique using a camera with a charge-coupled device (CCD), which was deemed more efficient technique compared to the conventional one. Through this technique, images could be displayed directly on the monitor without going through the film washing process. Edge detection methods were implemented in the algorithm program. It was the first step to complement the image information where edges characterize object boundaries. It is useful for the process of segmenting and identifying objects in neutron digital radiography images. The edge detection methods used in this study were Sobel, Prewitt, Canny, and Laplacian of Gaussian. According to the results of the image that have been tested for edge detection, the best image was carried out by the Canny operator because the method is more explicit. The obtained edges were more connected than the other methods which are still broken. The Canny technique provided edge gradient orientation which resulted in a proper localization.


2019 ◽  
Vol 2019 (1) ◽  
pp. 331-338 ◽  
Author(s):  
Jérémie Gerhardt ◽  
Michael E. Miller ◽  
Hyunjin Yoo ◽  
Tara Akhavan

In this paper we discuss a model to estimate the power consumption and lifetime (LT) of an OLED display based on its pixel value and the brightness setting of the screen (scbr). This model is used to illustrate the effect of OLED aging on display color characteristics. Model parameters are based on power consumption measurement of a given display for a number of pixel and scbr combinations. OLED LT is often given for the most stressful display operating situation, i.e. white image at maximum scbr, but having the ability to predict the LT for other configurations can be meaningful to estimate the impact and quality of new image processing algorithms. After explaining our model we present a use case to illustrate how we use it to evaluate the impact of an image processing algorithm for brightness adaptation.


2019 ◽  
Vol 29 (1) ◽  
pp. 1226-1234
Author(s):  
Safa Jida ◽  
Hassan Ouallal ◽  
Brahim Aksasse ◽  
Mohammed Ouanan ◽  
Mohamed El Amraoui ◽  
...  

Abstract This work intends to apprehend and emphasize the contribution of image-processing techniques and computer vision in the treatment of clay-based material known in Meknes region. One of the various characteristics used to describe clay in a qualitative manner is porosity, as it is considered one of the properties that with “kill or cure” effectiveness. For this purpose, we use scanning electron microscopy images, as they are considered the most powerful tool for characterising the quality of the microscopic pore structure of porous materials. We present various existing methods of segmentation, as we are interested only in pore regions. The results show good matching between physical estimation and Voronoi diagram-based porosity estimation.


2014 ◽  
Vol 643 ◽  
pp. 237-242 ◽  
Author(s):  
Tahari Abdou El Karim ◽  
Bendakmousse Abdeslam ◽  
Ait Aoudia Samy

The image registration is a very important task in image processing. In the field of medical imaging, it is used to compare the anatomical structures of two or more images taken at different time to track for example the evolution of a disease. Intensity-based techniques are widely used in the multi-modal registration. To have the best registration, a cost function expressing the similarity between these images is maximized. The registration problem is reduced to the optimization of a cost function. We propose to use neighborhood meta-heuristics (tabu search, simulated annealing) and a meta-heuristic population (genetic algorithms). An evaluation step is necessary to estimate the quality of registration obtained. In this paper we present some results of medical image registration


1991 ◽  
Author(s):  
Roger Davies ◽  
Bento A. B. Correia ◽  
Fernando D. Carvalho

2017 ◽  
Vol 20 (K3) ◽  
pp. 31-37
Author(s):  
Tien Van Tran ◽  
Cat Ngoc Phuong Phan ◽  
Linh Quang Huynh ◽  
Quynh Ngoc Nguyen ◽  
Hieu Trung Nguyen

Cervical pathologies are frequently occuring diseases and may affect women’s quality of life in many ways. These pathologies are curable with early detection and with a following suitable treatment plans. Colposcopy is a standard examination among screening methods which are used to early detect the abnormal lesions on cervix’s surface. Recently, studies about processing polarized image show ability to support diagnosis of the cervix. In this research, we use cervix’s polarized images and image processing algorithms to segment the blood distribution of Nabothian cyst and Trichomonas vaginalis infection. These results have the potential to provide underlying information of the cervix to support the diagnosis.


Author(s):  
Naoufel Khayati ◽  
Wided Lejouad-Chaari

In this paper, we present a distributed collaborative system assisting physicians in diagnosis when processing medical images. This is a Web-based solution since the different participants and resources are on various sites. It is collaborative because these participants (physicians, radiologists, knowledgebasesdesigners, program developers for medical image processing, etc.) can work collaboratively to enhance the quality of programs and then the quality of the diagnosis results. It is intelligent since it is a knowledge-based system including, but not only, a knowledge base, an inference engine said supervision engine and ontologies. The current work deals with the osteoporosis detection in bone radiographies. We rely on program supervision techniques that aim to automatically plan and control complex software usage. Our main contribution is to allow physicians, who are not experts in computing, to benefit from technological advances made by experts in image processing, and then to efficiently use various osteoporosis detection programs in a distributed environment.


In many image processing applications, a wide range of image enhancement techniques are being proposed. Many of these techniques demanda lot of critical and advance steps, but the resultingimage perception is not satisfactory. This paper proposes a novel sharpening method which is being experimented with additional steps. In the first step, the color image is transformed into grayscale image, then edge detection process is applied using Laplacian technique. Then deduct this image from the original image. The resulting image is as expected; After performing the enhancement process,the high quality of the image can be indicated using the Tenengrad criterion. The resulting image manifested the difference in certain areas, the dimension and the depth as well. Histogram equalization technique can also be applied to change the images color.


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