• Geophysics and Geophysical Exploration
• /
• v.14 no.3
• /
• pp.234-241
• /
• 2011

Recently, exploration and development of oil sands are thriving due to high oil price. Because oil sands reservoir usually exists as a thin layer, multicomponent VSP, which has the advantage of the high-resolution around the borehole, is more effective than surface seismic survey in exploring oil sand reservoir. In addition, prestack phase-screen migration is effective for multicomponent seismic data because it is based on an one-way wave equation. In this study, we examined the applicability of the prestack phase-screen migration for multicomponent RVSP data to image the thin oil sand reservoir. As a preprocessing tool, we presented a method for separating P-wave and PS-wave from multicomponent RVSP data by using incidence angle and rotation matrix. To verify it, we have applied the developed wavefield separation method to synthetic data obtained from the velocity model including a horizontal layer and dipping layers. Also, we compared the migrated image by using P-wave with that by using PS-wave. As a result, the PS-wave migrated image has higher resolution and wide coverage than P-wave migrated image. Finally, we have applied the prestack phase-screen migration to the synthetic data from the velocity model simulating oil sand reservoir in Canada. The results show that the PS-wave migrated image describe the top and bottom boundaries of the thin oil sand reservoir more clearly than the P-wave migrated image.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.6
• /
• pp.1143-1148
• /
• 2002

This paper analyses the transient response of a spherical elastic shell located near fee surface and impinged by spherical step-exponential acoustic shock waves. The problem is solved through extension of a method (Huang, 1969) previously formulated for the excitation in an infinite domain, which employs the classical separation of variables, series solutions, and Laplace transform technique The effect of the free surface reflection is taken into account using the image source method. The reflection of the incident wave has been treated by the same image formulation. If the reflection of the pressure field scattered and radiated by the shell is considered, the problem becomes that of multiple scattering by two spheres. However, this is in general negligible considering errors inherent from other sources and that the scattered and radiated pressure waves emanating from the shell are small. Thus, the problem is reduced to that of a structure immersed in an infinite fluid and impinged upon the origin and the image incident.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.5
• /
• pp.919-926
• /
• 2023

In this paper, we implemented the surveillance camera system capable of day and night shooting. To this end, it is designed to capture clear images even at night using a CMOS image sensor as well as an IR-LED. In addition, a relatively simple motion detection algorithm was proposed through color model separation. Motions can be detected by extracting only the H channel from the color model, dividing the image into blocks, and then applying the block matching method using the average color value between consecutive frames. When motions are detected during filming, an alarm sounds automatically and a day and night motion detection system is implemented that can capture and save the event screen to a PC.

• International Journal of Computer Science & Network Security
• /
• v.24 no.1
• /
• pp.163-177
• /
• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• The KIPS Transactions:PartB
• /
• v.10B no.4
• /
• pp.397-402
• /
• 2003

This paper proposes an efficient fixed-point (FP) algorithm for improving performances of the independent component analysis (ICA) based on neural networks. The proposed algorithm is the FP algorithm based on Newton method for ICA using the adaptive learning parameters. The purpose of this algorithm is to improve the separation speed and performance by using the learning parameters in Newton method, which is based on the first order differential computation of entropy optimization function. The learning rate and the moment are adaptively adjusted according to an updating state of inverse mixing matrix. The proposed algorithm has been applied to the fingerprints and the images generated by random mixing matrix in the 8 fingerprints of 256${\times}$256-pixel and the 10 images of 512$\times$512-pixel, respectively. The simulation results show that the proposed algorithm has the separation speed and performance better than those using the conventional FP algorithm based on Newton method. Especially, the proposed algorithm gives relatively larger improvement degree as the problem size increases.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.22 no.3
• /
• pp.373-385
• /
• 1998

The local Nusselt numbers have been measured for a round turbulent jet impinging on the convex surface with and without rib. Liquid crystal/transient method was used to determine the Nusselt number distributions along the surface. The temperature on the surface was measured to within .+-.0.25 deg. C accuracy using liquid crystal and a digital color image processing system. The experiments were made for the jet Reynolds number (Re) 23,000, the dimensionless nozzle-to-surface distance (L/d) from 6 to 10, the dimensionless surface curvature (d/D) 0.056, and the various rib types (height(d$_{1}$) from 1 to 2 mm, pitch (p) from 6 to 32 mm). It was found that the average Nusselt numbers on the convex surface with rib are higher than those without rib, mainly due to an increase in the turbulent intensity caused by flow separation, recirculation and reattachment on the wall surface. In addition, we compared the results by the steady-state method using the gold-film Intrex with those by the transient method.

• Geophysics and Geophysical Exploration
• /
• v.26 no.4
• /
• pp.171-184
• /
• 2023

Machine learning (ML)-based cavity detection using a large amount of survey data obtained from vehicle-mounted ground penetrating radar (GPR) has been actively studied to identify underground cavities. However, only simple image processing techniques have been used for preprocessing the ML input, and many conventional seismic and GPR data processing techniques, which have been used for decades, have not been fully exploited. In this study, based on the idea that a cavity can be identified using diffraction, we applied ML-based diffraction separation to GPR data to increase the accuracy of cavity detection using the YOLO v5 model. The original ML-based seismic diffraction separation technique was modified, and the separated diffraction image was used as the input to train the cavity detection model. The performance of the proposed method was verified using public GPR data released by the Seoul Metropolitan Government. Underground cavities and objects were more accurately detected using separated diffraction images. In the future, the proposed method can be useful in various fields in which GPR surveys are used.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2000.11a
• /
• pp.457-460
• /
• 2000

Injection molding is the most widely used process for the industrial forming of plastic articles. During an injection molding process of composites, the fiber-matrix separation and fiber orientation are caused by the flow of molten polymer/fiber mixture. As a result, the product tends to be nonhomogeneous and anisotropic. Hence, it is very important to clarify the relations between separation·orientation and infection molding conditions. So far, there is no research on the measurement of fiber orientation using image processing. In this study, the effects of fiber content ratio and molding condition on the fiber orientation-angle distributions are studied experimentally. Using the image processing method, the fiber orientation distribution of welding parts in injection-molded products is assessed. And the effects of fiber content and injection mold shapes on the fiber orientation in case of fiber reinforced polymeric composites are studied. experimentally.

• The KIPS Transactions:PartB
• /
• v.11B no.7 s.96
• /
• pp.813-820
• /
• 2004

This paper proposes a digital image watermarking which is robust to geometric distortions using an independent component analysis(ICA) of fixed-point(FP) algorithm based on secant method. The FP algorithm of secant method is applied for better performance in a separation time and rate, and ICA is applied to reject the prior knowledges for original image, key, and watermark such as locations and size, etc. The proposed method embeds the watermark into the spatial domain of original image The proposed watermarking technique has been applied to lena, key, and two watermarks(text and Gaussian noise) respectively. The simulation results show that the proposed method has higher speed and better rate for extracting the original images than the FP algorithm of Newton method. And the proposed method has a watermarking which is robust to geometric distortions such as resizing, rotation, and cropping. Especially, the watermark of images with Gaussian noise has better extraction performance than the watermark with text since Gaussian noise has lower correlation coefficient than the text to the original and key images. The watermarking of ICA doesn't require the prior knowledge for the original images.

• Journal of Digital Policy
• /
• v.2 no.3
• /
• pp.1-7
• /
• 2023

In this paper, I proposes a method for performing single image super resolution by separating texture-spatial domains and then classifying features based on detailed information. In CNN (Convolutional Neural Network) based super resolution, the complex procedures and generation of redundant feature information in feature estimation process for enhancing details can lead to quality degradation in super resolution. The proposed method reduced procedural complexity and minimizes generation of redundant feature information by splitting input image into two channels: texture and spatial. In texture channel, a feature refinement process with step-wise skip connections is applied for detail restoration, while in spatial channel, a method is introduced to preserve the structural features of the image. Experimental results using proposed method demonstrate improved performance in terms of PSNR and SSIM evaluations compared to existing super resolution methods, confirmed the enhancement in quality.