• Journal of the Korean earth science society
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• v.26 no.1
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• pp.58-65
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• 2005

Homomorphic filtering improves image by enhancing high components and reducing low components in the Sequency domain based on FFT, as one of useful digital image processing techniques. In this study, the application program f3r homomorphic filtering was developed. Using this program, satellite imageries and geophysical image such as magnetic image data were processed and their results were analyzed. In case of applying to other techniques suck as histogram equalization and kernel-based masking f3r the same purpose. they often cause the slight distortion of boundary or overall change of brightness values on the whole image. Whereas. homomorphic filtering has ability to enhance selectively detailed components in a target image. Therefore. this technique can be effectively used for extraction or separation of complex types of characteristics contained in the satellite imagery. In addition, this technique would be applicable to investigate anomalous zone in various geophysical image data.

• Spatial Information Research
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• v.19 no.1
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• pp.117-126
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• 2011

Recently, AR applications provide location-based spatial information by GPS. Also, the spatial information is displayed by the angle of the camera. So far, traditional spatial indexes in spatial database field retrieve and filter spatial information by the minimum bounding rectangle (MBR) algorithm.(ex. R-tree) MBR strategy is a useful technique in the geographic information systems and location based services. But MBR technique doesn't reflect the characteristics of spatial queries in AR. Spatial queries of AR applications have high possibility of the dead space area between MBRs of non-leaf node and query area. We propose triangle node filtering algorithm that improved efficiency of spatial retrieval used the triangle node filtering techniques by exclusion the dead space. In this paper, the proposed algorithm has been implemented on PostgreSQL/PostGIS. Experimental results show the spatial retrieval that using the proposed algorithm better performance than the spatial retrieval that of the minimum bounding rectangle algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.380-388
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• 2019

Jet engine modulation(JEM) signals are widely used for target recognition. These signals coming from a potentially hostile aircraft provide specific information about the jet engine. In order to obtain the number of blades, which is uniquely provided by the JEM signal, one must extract the spool rate, which is the rotation speed of the blades. In this paper, we propose an algorithm to extract the spool rate from a weak JEM signal. A criterion is developed to extract the spool rate from the JEM signal by analyzing the intensity of the JEM signal component. The weak signal is first subjected to a high-pass filtering-based process, which modifies it to facilitate spool rate extraction. We then apply a peak detection process and extract the spool rate. The technique is simpler than the existing CEMD or WD method, is accurate, and greatly reduces the time required.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.93-100
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• 2022

In the era of information overload on the Internet, the recommendation system, which is an indispensable function, is a service that recommends products that a user may prefer, and has been successfully provided in various commercial sites. Recently, studies to reflect the rating time of items to improve the performance of collaborative filtering, a representative recommendation technique, are active. The core idea of these studies is to generate the recommendation list by giving an exponentially lower weight to the items rated in the past. However, this has a disadvantage in that a time function is uniformly applied to all items without considering changes in users' preferences according to the characteristics of the items. In this study, we propose a time-aware collaborative filtering technique from a completely different point of view by developing a new similarity measure that integrates the change in similarity values between items over time into a weighted sum. As a result of the experiment, the prediction performance and recommendation performance of the proposed method were significantly superior to the existing representative time aware methods and traditional methods.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.149-155
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• 2022

The popularity of e-commerce systems on the Internet is increasing day by day, and the recommendation system, as a core function of these systems, greatly reduces the effort to search for desired products by recommending products that customers may prefer. The collaborative filtering technique is a recommendation algorithm that has been successfully implemented in many commercial systems, but despite its popularity and usefulness in academia, the memory-based implementation has inaccuracies in its reference neighbor. To solve this problem, this study proposes a new time-aware collaborative filtering technique that integrates and utilizes the neighbors of each item and each user, weighting the recent similarity more than the past similarity with them, and reflecting it in the recommendation list decision. Through the experimental evaluation, it was confirmed that the proposed method showed superior performance in terms of prediction accuracy than other existing methods.

• Proceedings of the KAIS Fall Conference
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• 2000.04a
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• pp.56-56
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• 2000

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.11
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• pp.1307-1314
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• 2012

To reduce the effects of clutters with subsurface inhomogenities in ground-penetrating radar(GPR) images, an eigenimage based signal-processing technique is presented. If the conventional eigenimage filtering technique is applied to B-scan images of a GPR survey, relatively homogeneous clutters such as antenna ringing, direct coupling between transmitting and receiving antennas, and soil-surface reflection, can be removed sufficiently. However, since random clutters of subsurface inhomogenities still remain in the images, target signals are distorted and obscured by the clutters. According to a comparison of the eigenimage filtering results, there is different coherency between subsurface clutters and target signals. To reinforce the pixels with high coherency and reduce the pixels with low coherency, the pixel-by-pixel geometric-mean process after the eigenimage filtering is proposed here. For the validity of the proposed approach, GPR survey for detection of a metal target in a randomly inhomogeneous soil is numerically simulated by using a random media generation technique and the finite-difference time-domain(FDTD) method. And the proposed signal processing is applied to the B-scan data of the GPR survey. We show that the proposed approach provides sufficient enhancement of target signals as well as remarkable reduction of subsurface inhomogeneous clutters in comparison with the conventional eigenimage filtering.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.138-149
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• 2006

As the environment with sensor network and ubiquitous computing is emerged, there are many demands of handling continuous, fast data such as streaming data. As work about streaming data has begun, work about management of streaming data in Publish-Subscribe system is started. The recent emergence of XML as a standard for information exchange on Internet has led to more interest in Publish - Subscribe system. A filtering technique of streaming XML data in the existing Publish- Subscribe system is using some schemes based on automata and YFilter, which is one of filtering techniques, is very popular. YFilter exploits commonality among path queries by sharing the common prefixes of the paths so that they are processed at most one and that is using the top-down approach. However, because partial matching path queries interrupt the common prefix sharing and don't calculate from root, throughput of YFilter decreases. So we use sharing of commonality among path queries with the common postfixes of the paths and use the bottom-up approach instead of the top-down approach. This filtering technique is called as PoSFilter. And we verify this technique through comparing with YFilter about throughput.

• Journal of Biomedical Engineering Research
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• v.32 no.3
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• pp.245-250
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• 2011

Parallel imaging technique can provide several advantages for a multitude of MRI applications. Especially, in SENSE technique, sensitivity maps were always required in order to determine the reconstruction matrix, therefore, a number of difference approaches using sensitivity information from coils have been demonstrated to improve of image quality. Moreover, many filtering methods were proposed such as adaptive matched filter and nonlinear diffusion technique to optimize the suppression of background noise and to improve of image quality. In this study, we performed SENSE reconstruction using computer simulations to confirm the most suitable method for the feasibility of filtering effect and according to changing order of polynomial fit that were applied on variation of spatial resolution of sensitivity map. The image was obtained at 0.32T(Magfinder II, Genpia, Korea) MRI system using spin-echo pulse sequence(TR/TE = 500/20 ms, FOV = 300 mm, matrix = $128{\times}128$, thickness = 8 mm). For the simulation, obtained image was multiplied with four linear-array coil sensitivities which were formed of 2D-gaussian distribution and the image was complex white gaussian noise was added. Image processing was separated to apply two methods which were polynomial fitting and filtering according to spatial resolution of sensitivity map and each coil image was subsampled corresponding to reduction factor(r-factor) of 2 and 4. The results were compared to mean value of geomety factor(g-factor) and artifact power(AP) according to r-factor 2 and 4. Our results were represented while changing of spatial resolution of sensitivity map and r-factor, polynomial fit methods were represented the better results compared with general filtering methods. Although our result had limitation of computer simulation study instead of applying to experiment and coil geometric array such as linear, our method may be useful for determination of optimal sensitivity map in a linear coil array.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.297-299
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• 2017

Recently, the application fields of augmented reality(AR) are rapidly increasing, and related contents are also increasing in demand. In this way, object-based marker recognition is required for service of AR contents in mobile environment. At this time, in order to provide information corresponding to the marker, a technique of generating and servicing a virtual object corresponding to a specific marker is used. However, when a virtual object corresponding to a marker is held on the AR screen, a phenomenon occurs that an object of the marker unstably shakes due to various reasons such as camera shake and camera movement. As described above, the AR service based on the mobile device has a problem that it is difficult to represent objects stably. In this paper, we propose a stable marker recognition and tracking technique by applying the filtering technique according to the physical state change of the device when recognizing fixed markers in mobile AR environment.