جستجوی مقالات مرتبط با کلیدواژه « Image processing » در نشریات گروه « فیزیک »

A large number of printed board circuits (PCBs) are analyzed by X-ray imaging in reverse engineering for the purpose of identifying their connections, their damage, and how they are linked together. Using this method, an X-ray is passed through single or multi-layer boards in order to determine how they are connected and how the parts are arranged. According to the findings, there is fogging in the radiographs due to X-ray scattering and the thinness of copper connections on the boards as well as the small sizes of electronic components. This research employs the Modified Total Variation method (MTV) with alternating gradient, which is an iterative method based on gradient changes in Total Variation, to increase contrast. Based on the results of the implementation of the MTV algorithm on radiographs of various ranges, the contrast has increased, and besides the copper connections, the internal components of the electronic components have also become clearer. Reconstructed images show a contrast improvement of approximately 20 to 40%, according to experts. Using this information, it is possible to repair or build boards in reverse engineering.

Measuring the concentration of sediments on beaches is of particular importance in line with the implementation of beach management plans. Coastal currents, especially those caused by breaking waves on the intermediate beaches, are considered one of the most important phenomena in the sediments transport and pollutant emissions in seas and coastal environments. In this research, first the complex pattern of these currents was implemented in beaches with an intermediate state in laboratory conditions. Then, using the governing empirical formulas, the concentration of sediments in each run was calculated under the sediment suspension mechanism due to the turbulent movement caused by broken waves. In the next step, using image processing principles in the Matlab software, the color characteristics of the images at different depths and hydrodynamic conditions were extracted to estimate the surface Suspended Sediment Concentration. The main results of this research show the high correlation of the color features of the images with the concentration of sediments in the area based on the algorithms presented in the RGB and Grayscale models. The accuracy of the results presented in different parts of the near shore zone indicates the fact that the accuracy of the model results decreases by moving towards the beach face and the best fit of the features of the images and the amount of sediment concentration is seen in the shoaling region.

Neutron Computed Tomography (nCT) is one of the modern applications of research reactors. The combination of the Three-dimensional representation capability of tomographic imaging and the unique properties of neutron interaction with materials creates valuable information about the internal structure of materials and components. In this study, the effect of data acquisition geometry and method of image reconstruction on tomographic images of the Tehran Research Reactor Imaging Facility (TRRIF) have been investigated based on contrast and the ratio of contrast to noise parameters. In experimental data acquisition, two radiation geometries have been aligned with angular steps of 1 and 0.5 degrees, respectively. Two samples were turned within the neutron radiation field at a half-screen. Image reconstruction has been performed through FBP and ART, SART, and SIRT algorithms, using Python programming language. The stack of images has been rendered to gain sample volume. Initially, in order to reconstruct the image through a high-quality set of projections, experimental data acquisition parameters have been optimized. Then, pre-processing has been carried out on projections. The results showed that the sample components and some defects could be differentiated from each other. Contrast and CNR were improved in data acquisition geometry with smaller angular steps and through SIRT reconstruction method.

This radiological monitoring system consisting of a 2-inch NaI(Tl) crystal coupled to a PM tube and mounted on a multi-rotor UAV has been developed to fast detect radioactive sources. To assess its performance, a set of experiments for the detection of low-level Co-60 and Cs-137 point sources in a soccer field was performed. Then, the radiological map was made and then fused with the geographical one using image processing techniques. The results show that at 50 cm, all 5-point sources were successfully identified in their actual locations. By decreasing the flight height, the ability of the drone-based radiological monitor in recognizing radioactive sources significantly increases. The results confirmed that the drone system with the scintillation detector enabled the accurately identifying radiological anomalies by surveying a contaminated area.

X-rays and neutron radiography images are one of the most effective defects and structure detection methods. The interactions between neutrons and X-rays are different in the material, and therefore, different information can be obtained from the radiographs. Due to neutron and X-rays photon scattering, focal spot size, electronic noises, etc., the images are blurred and their quality is reduced. In this study, while investigating the radiographs of X-rays, and neutrons, the defects and internal structure of objects are investigated. The results show that neutron radiography performs very well in detecting the internal structure of low atomic number materials. X-ray radiography is effective for high atomic numbers as metal. Gaussian convolution is used to enhance the radiography images and reduce blurriness components. The results show that by reducing the background, the blurriness components can be reduced and the defects areas and internal structure of the objects can be better investigated. Specialists evaluated the results in radiography; the results show that the expert’s evaluation approved the image enhancement.

The significant defects in the artistic paints are rupture, scratches, and twisting, which are caused by variations in temperature, exposure to moisture, and erosion. Industrial radiography can detect the defect locations, which is a non-destructive test, can be carried out. In radiography testing (RT), the produced radiographs may suffer from some degree of blurriness and low contrast due to the inherent scattering of X-ray, geometric factors such as the size of the beam source, the thickness of the part, and the source to film distance (SFD). The diagnosis of the shapes and sizes of the damages is difficult in some cases. Image processing methods can be used as additional tools for enhancing image quality and more accessible interpretation. In the present study, a Gabor filter technique, based on wavelet analysis with an automatic threshold level, was used to reduce the fogginess of radiographs. The reconstructed images of the proposed algorithm have better contrast, and the defects and signs are more precise than the original image. This algorithm can help the restoration experts for repairing the artistic paintings.

Since it is too vital to the prevention of carotid disease in the vascular system, it seems necessary to the estimation of the elastic behavior of the carotid artery in head and neck external radiotherapy. In the present study, a total of 24 neck carcinoma patients treated with external radiotherapy had been studied. The carotid mean dose values were determined for each case by contouring the common carotid artery in consecutive CT scan images. Ultrasonography was performed from the wall region of each subject before and after the radiotherapy process. The instantaneous changes of intima-media thickness and radial movements in the arterial wall were extracted by the implementation of a maximum gradient algorithm. The results indicate that the normalized rate of absorbed dose of carotid from prescriptive dose is about 0.82±0.24. Moreover, the normalized value of Young modulus of radiation-induced carotids compared to non-irradiated carotid arteries along with increasing the intima-media-thickness is 1.58±0.21. These changes may be lead to stroke symptoms in the future.

In this work, we report on update and automation of an old-fashioned interferometer by using image processing techniques and developing a Graphical User Interface (GUI) in the MATLAB environment. After updating the system and receiving the digital images of interference fringe patterns from the interferometer and their transfer to the MATLAB environment, the ability of image rotation, as a geometric operation, is provided in the GUI. Following the detection of the dominant noise in the received images, digital filters that best suited for their remove and image enhancement are identified. It is found that the two image processing filters, which have the best results in removing the noises, are the linear average and the nonlinear median filters. The possibility of chossing these two filters along with their corresponding neighborhoods are provided in the GUI. To automate the system and for machine vision detection of optical surface qualities, an algorithm is developed to detect the interference fringes and to determine the space between them. The accuracy of the algorithm and the developed GUI in measuring the quality of the optical elements is tested by using the known standard quality elements. It is found that the GUI is capable of measuring the optical quality with good precision.

Image prosseing methods is useful for extraction of the defects such as porosity, slag and crack in the noisy and low contrast industrial radiography images. It is noticeable that the defects appear as the gradients in pixel values, therefore, the gradient based method can help to detect the defects. In this research, different methods of gradient extraction such as Soble, Perwitt and the nonlinear diffusion filter were implemented and tried to improve the edges and the defect detection. The nonlinear diffusion filter method depends on diffusion coefficient, k, and the chosen value for k can affect the exact smoothing of the edges. Thus, in this attempt, by the use of a new approach, in comparison with the conventional edge finder methods, a nonlinear diffusion filter method is repeated and the edges are smoothed in the obtained images. Then, the defects in the gradient of images are extracted by substracting the original image from the obtained image. The mentioned methods were implemented in different radiography images. The results show that the proposed method in comparison with local gradient ones such as Sobel and Perwitt methods has superiority over different radiographic images as confirmed by the radiography film interpreters.

Mammography is the most effective method for the early diagnosis of breast cancer diseases. As mammographic images contain low signal to noise ratio and low contrast, it becomes too difficult for radiologists to analyze mammogram. To deal with the above stated problems, it is very important to enhance the mammographic images using image processing methods. This paper introduces a new image enhancement approach for mammographic images which uses the modified mathematical morphology, wavelet transform and homomorphic filter to suppress the noise of images. For performance evaluation of the proposed method, contrast improvement index (CII) and edge preservation index (EPI) are adopted. Experimental results on mammographic images from Pejvak Digital Imaging Center (PDIC) show that the proposed algorithm improves the two indexes, thereby achieving the goal of enhancing mammographic images.

Arrays of dielectric barrier discharge are used for control of various aerodynamic phenomena such as control flow separation. In order to control this phenomenon by the generated momentum، it is needed to determine the maximum discharge voltage required to the momentum generation. By image processing، maximum momentum produced and consequently maximum discharge voltage can be determined with using plasma flame length and light intensity. The advantage of this method compared to other methods is simplicity and availability of a camera as the only required equipment. In this study، an array of 8DBD actuators arranged perpendicular to flow on NACA0012 is installed in a wind tunnel. Performance and maximum discharge voltage can be determined by processing the images captured from the arrays in different discharge voltages and dynamic pressures. Using image processing method for evaluating the efficiency of DBD actuators and accessing the maximum discharge voltage for flow separation control is unprecedented.

Industrial Radiography is one of the most important methods to detect weld defects such as porosity, slag and crack. The interpretation of radiographic films characterizes the weld defects. The defect detection depends on radiographic film quality and the expert of interpreter. If the provided images of the industrial radiography are not clear, the detection of the defect can be difficult. But the radiographic image is usually noisy and has low quality. Thus, it is requred to use methods that can detect the defect accurately. The use of image processing techniques is available to achieve this aim. It is noticed that human eye is used to see objects in three dimensions and can also detect the depth. Thus, in this research, the shape from the shading (SFS) method is applied for two-dimensional radiographic images to extract three-dimensional ones. For the evaluation, the experts’ opinions in radiography have also been considered. The results of comments indicate that using the SFS method is valuable to improve the defects detection in weld radiography.

Radiography is known as one of the oldest and most widely used nondestructive testing (NDT) techniques, where it introduces the most appreciated technique by producing images which are acting as unique fingerprint records of samples of interest. Among the interesting applications of radiography are archeological and art applications. In this research, radiography was implemented for identification of a damaged art-historical material. The sample was a brass plate belonging to Iran cultural heritage. The estimated age of the plate was about 3500 years. The plate was discovered in Lorestan province, where it is generally called “Lorestan bronze”. The plate was damaged seriously due to serious corrosion enviromental attacks, and recognition of the sample was considered as the major problem. The simple radiography method was quite helpful for the plate determination but the method  suffered from some major drawbacks due to contrast and thickness measurements. The thickness measurement and corrosion/erosion evaluation were the vital components of the inspection. The image processing techniques and precise thickness measurement method were added to the digitized radiographs. For the digital image processing, a histogram matching algorithm and an edge detection method were used. After all, the resulted image showed an enhanced quality image of the original traces of the hammered design. The results showed that a good experimental setup of radiography along with the image processing technique can give a high quality radiographic image which is able to be used effectively for the identification of art antiques. The human evaluation results also confirmed the ability of the proposed method with a high degree of certainty.