• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.410-418
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• 2023

Recently, advancements and commercialization in the field of maritime autonomous surface ships (MASS) has rapidly progressed. Concurrently, studies are also underway to develop methods for automatically surveying the condition of various on-board equipment remotely to ensure the navigational safety of MASS. One key issue that has gained prominence is the method to obtain values from analog gauges installed in various equipment through image processing. This approach has the advantage of enabling the non-contact detection of gauge values without modifying or changing already installed or planned equipment, eliminating the need for type approval changes from shipping classifications. The objective of this study was to identify a dynamically changing indicator needle within noisy images of analog gauges. The needle object must be identified because its position significantly affects the accurate reading of gauge values. An analog pressure gauge attached to an emergency fire pump model was used for image capture to identify the needle object. The acquired images were pre-processed through Gaussian filtering, thresholding, and morphological operations. The needle object was then identified through Hough Transform. The experimental results confirmed that the center and object of the indicator needle could be identified in images of noisy analog gauges. The findings suggest that the image processing method applied in this study can be utilized for shape identification in analog gauges installed on ships. This study is expected to be applicable as an image processing method for the automatic remote survey of MASS.

• Journal of the military operations research society of Korea
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• v.33 no.1
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• pp.93-103
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• 2007

Ship identification systems currently employed provide the underwater sound analysis, analyzed data saving and user interface with comparison function. But final analysis and identification depend only on experts. Therefore, the reliability of these identification systems relies on user's ability on information recognition. This paper presents the method of recognition for the purpose of providing the basic data for an automatic ship class identification. we get the underwater sounds using the PC. We use Matlab in order to reduce ambient noises, take out an acoustic characteristics using the pattern recognition, and classify the ships.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.75-81
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• 2012

Road identification is the important task for extracting a road region from the high-resolution satellite images, when the road candidates is extracted by the pre-processing tasks using a binarization, noise removal, and color processing. Therefore, we propose a noble approach for identifying a road using the orientation-selective spatial filters, which is motivated by a computational model of neuron cells found in the primary visual cortex. In our approach, after the neuron cell typed spatial filters is applied to the isolated connected-labeling road candidate regions, proposed method identifies the region of perceiving the strong orientation feature with the real road region. To evaluate the effectiveness of the proposed method, the accuracy&error ratio in the confusion matrix was measured from road candidates including road and non-road class. As a result, the proposed method shows the more than 92% accuracy.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.15-24
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• 2008

For high-dimensional classification tasks, such as face recognition, the number of samples is smaller than the dimensionality of the samples. In such cases, a problem encountered in linear discriminant analysis-based methods for dimension reduction is what is known as the small sample size (SSS) problem. Recently, to solve the SSS problem, a way of employing a dissimilarity-based classification(DBC) has been investigated. In DBC, an object is represented based on the dissimilarity measures among representatives extracted from training samples instead of the feature vector itself. In this paper, we propose a new method of optimizing DBCs using multi-level fusion strategies(MFS), in which fusion strategies are employed to represent features as well as to design classifiers. Our experimental results for benchmark face databases demonstrate that the proposed scheme achieves further improved classification accuracies.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.201-210
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• 2023

Deep learning-based face verificattion model show high performance and are used in many fields, but there is a possibility the user's face image may be leaked in the process of inputting the face image to the model. Althoughde-identification technology exists as a method for minimizing the exposure of face features, there is a problemin that verification performance decreases when the existing technology is applied. In this paper, after combining the face features of other person, a de-identified face image is created through StyleGAN. In addition, we propose a method of optimizingthe combining ratio of features according to the face verification model using HopSkipJumpAttack. We visualize the images generated by the proposed method to check the de-identification performance, and evaluate the ability to maintain the performance of the face verification model through experiments. That is, face verification can be performed using the de-identified image generated through the proposed method, and leakage of face personal information can be prevented.

• The Journal of the Acoustical Society of Korea
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• v.16 no.6
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• pp.25-35
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• 1997

Most of speech analysis methods developed up to date are based on second order statistics, and one of the biggest drawback of these methods is that they show dramatical performance degradation in noisy environments. On the contrary, the methods using higher order statistics(HOS), which has the property of suppressing Gaussian noise, enable robust feature extraction in noisy environments. In this paper we propose a text-independent speaker identification system using higher order statistics and compare its performance with that using the conventional second-order-statistics-based method in both white and colored noise environments. The proposed speaker identification system is based on the vector quantization approach, and employs HOS-based voiced/unvoiced detector in order to extract feature parameters for voiced speech only, which has non-Gaussian distribution and is known to contain most of speaker-specific characteristics. Experimental results using 50 speaker's database show that higher-order-statistics-based method gives a better identificaiton performance than the conventional second-order-statistics-based method in noisy environments.

• The KIPS Transactions:PartD
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• v.9D no.4
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• pp.561-570
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• 2002

In order to evaluate the performance of incremental update algorithms, we perform experimental tests on the time of updating view objects. In this paper, the incremental update algorithms are evaluated on two kinds of materialized methods : materialization by value-copy and materialization by preserving object identifiers (OIDs). The result of performance evaluation shows that there is little difference in the updating time of view objects between two materialization methods. The evaluation of query processing on spatial views shows that materialization by value-copy is much better than materialization by preserving OIDs. As the results of overall performance evaluation, it is more desirable to use the incremental update method based on materialization by value-copy than the incremental update method based on materialization by preserving OIDs.

• The Journal of the Acoustical Society of Korea
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• v.22 no.2
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• pp.153-161
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• 2003

In this paper, we propose a wavelet-based detection method to identify efficiently the time-delay or multipath channel of ocean acoustic signals due to complex ocean medium and boundary layers. Our proposed method employs wavelet packet transform to analyze the received broadband acoustic signals and applies the matched filter to determine the time region of interest. Also, we present numerical testing that results on both the simulated and real data revealed the efficiency of this method in time-delay estimation and moreover its capability in estimating the time-delay of individual path in multipath channel, in which the arrival patterns are too close to be separated by the matched filter method.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.3
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• pp.125-138
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• 2016

The service identification in service-oriented developments has been conducted by based on workflow, goals, scenarios, usecases, components, features, and patterns. However, the identification of service by semantic approach at the business value view was not detailed yet. In order to enhance accuracy of identifying business service, this paper proposes a method for identifying business service by analyzing syntax and semantics in XL-BPMN model. The business processes based on business scenario are identified, and they are designed in a XL-BPMN business process model. In this business process model, an unit business service is identified through binding closely related activities by the integrated analysis result of syntax patterns and properties-based semantic similarities between activities. The method through XL-BPMN model at upper business levels can identify the reusable unit business service with high accuracy and modularity. It also can accelerate more service-oriented developments by reusing identified services.

• The KIPS Transactions:PartD
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• v.13D no.1 s.104
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• pp.67-74
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• 2006

The security requirements identification in the software development has received some attention recently. However, previous methods do not provide clear method and process of security requirements identification. We propose a process that software developers can build application specific security requirements from state transition diagrams at the security threat location. The proposed process consists of building model and identifying application specific security requirements. The state transition diagram is constructed through subprocesses i) the identification of security threat locations using security failure data based on the point that attackers exploit software vulnerabilities and attack system assets, ii) the construction of a state transition diagram which is usable to protect, mitigate, and remove vulnerabilities of security threat locations. The identification Process of application specific security requirements consist of i) the analysis of the functional requirements of the software, which are decomposed into a DFD(Data Flow Diagram; the identification of the security threat location; and the appliance of the corresponding state transition diagram into the security threat locations, ii) the construction of the application specific state transition diagram, iii) the construction of security requirements based on the rule of the identification of security requirements. The proposed method is helpful to identify the security requirements easily at an early phase of software development.