• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.797-804
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• 2003

Scene change detection algorithm, which is very important preprocessing technique for video indexing and retrieval and determines the performance of video database system, is being studied widely. In this paper, we propose a more effective abrupt scene change detection, which is robust to large motion, sudden change of light and successive abrupt shot transitions rapidly. And we also propose a new gradual scene change detection algorithm, which can detect dissolve, and fade in/out precisely. Furthermore, we also propose a representative frame extraction algorithm which performs content-based video summary by novel DCT DC image buffering technique and accumulative histogram intersection measure (AHIM).

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.1050-1060
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• 2011

With increasing need for indexing of persons in a large video database, automatic indexing has been attracting great interest which takes advantage of automatic tagging instead of the time-consuming and costly manual tagging. However, automatic indexing approach should provide a degree of recognition proximity because it cannot identify the persons with accuracy of 100%. In this paper, we propose an efficient storage method for storing posting lists efficiently and a novel ranking technique of ordering relevant videos for efficient retrieval. Through experiment evaluations we have shown that our storage method exhibits good performance in compressing the posting list. We have also shown that the proposed ranking method is effective for finding relevant videos.

• Journal of Multimedia Information System
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• v.3 no.2
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• pp.35-42
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• 2016

Electrocardiogram (ECG) signal gives a clear indication whether the heart is at a healthy status or not as the early notification of a cardiac problem in the heart could save the patient's life. Several methods were launched to clarify how to diagnose the abnormality over the ECG signal waves. However, some of them face the problem of lack of accuracy at diagnosis phase of their work. In this research, we present an accurate and successive method for the diagnosis of abnormality through Discrete Wavelet Transform (DWT), QRS complex detection and Support Vector Machines (SVM) classification with overall accuracy rate 95.26%. DWT Refers to sampling any kind of discrete wavelet transform, while SVM is known as a model with related learning algorithm, which is based on supervised learning that perform regression analysis and classification over the data sample. We have tested the ECG signals for 10 patients from different file formats collected from PhysioNet database to observe accuracy level for each patient who needs ECG data to be processed. The results will be presented, in terms of accuracy that ranged from 92.1% to 97.6% and diagnosis status that is classified as either normal or abnormal factors.

• Journal of Multimedia Information System
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• v.9 no.1
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• pp.21-32
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• 2022

Early-stage diagnosis of Alzheimer's Disease (AD) from Cognitively Normal (CN) patients is crucial because treatment at an early stage of AD can prevent further progress in the AD's severity in the future. Recently, computer-aided diagnosis using magnetic resonance image (MRI) has shown better performance in the classification of AD. However, these methods use a traditional machine learning algorithm that requires supervision and uses a combination of many complicated processes. In recent research, the performance of deep neural networks has outperformed the traditional machine learning algorithms. The ability to learn from the data and extract features on its own makes the neural networks less prone to errors. In this paper, a dense neural network is designed for binary classification of Alzheimer's disease. To create a classifier with better results, we studied result of different activation functions in the prediction. We obtained results from 5-folds validations with combinations of different activation functions and compared with each other, and the one with the best validation score is used to classify the test data. In this experiment, features used to train the model are obtained from the ADNI database after processing them using FreeSurfer software. For 5-folds validation, two groups: AD and CN are classified. The proposed DNN obtained better accuracy than the traditional machine learning algorithms and the compared previous studies for AD vs. CN, AD vs. Mild Cognitive Impairment (MCI), and MCI vs. CN classifications, respectively. This neural network is robust and better.

• Journal of Multimedia Information System
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• v.8 no.4
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• pp.233-242
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• 2021

Various anatomical MRI imaging biomarkers for Alzheimer's Disease (AD) identification have been recognized so far. Cortical and subcortical volume, hippocampal, amygdala volume, and genetics patterns have been utilized successfully to diagnose AD patients from healthy. These fundamental sMRI bio-measures have been utilized frequently and independently. The entire possibility of anatomical MRI imaging measures for AD diagnosis might thus still to analyze fully. Thus, in this paper, we merge different structural MRI imaging biomarkers to intensify diagnostic classification and analysis of Alzheimer's. For 54 clinically pronounce Alzheimer's patients, 58 cognitively healthy controls, and 99 Mild Cognitive Impairment (MCI); we calculated 1. Cortical and subcortical features, 2. The hippocampal subfield, amygdala nuclei volume using Freesurfer (6.0.0) and 3. Genetics (APoE ε4) biomarkers were obtained from the ADNI database. These three measures were first applied separately and then combined to predict the AD. After feature combination, we utilize the sequential feature selection [SFS (wrapper)] method to select the top-ranked features vectors and feed them into the Multi-Kernel SVM for classification. This diagnostic classification algorithm yields 94.33% of accuracy, 95.40% of sensitivity, 96.50% of specificity with 94.30% of AUC for AD/HC; for AD/MCI propose method obtained 85.58% of accuracy, 95.73% of sensitivity, and 87.30% of specificity along with 91.48% of AUC. Similarly, for HC/MCI, we obtained 89.77% of accuracy, 96.15% of sensitivity, and 87.35% of specificity with 92.55% of AUC. We also presented the performance comparison of the proposed method with KNN classifiers.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.298-300
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• 2003

A management information system of the Nanji Islands National Marine Reserve is designed and constructed based on method of integration of remote sensing and geographic information system (GIS). The system consists of two sub-systems, dynamic monitoring information system and general database system. The former is used for storage and manage fundamental geographical data (topographical and bathymetric map), satellite remote sensing data (IKONOS, SPOT, IRS, NOAA and SeaWiFS etc.) and multimedia data. The latter is used for storage and manage resource data (shellfish and alga etc.), environmental data (meteorological and hydrologic) and in situ data. As part of electronic government, this system will be submitted to local government for monitoring, management and decision.

• Archives of design research
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• v.13 no.3
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• pp.313-320
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• 2000

Currently, The new wave of information technology has enormously influenced every field. In the Held of design, it is time to strive possible efforts in order to accumulate the design-related knowledge by maintaining, managing and controlling design information in a systematic manner, getting out of the old stage of mere use of data itself. Due to remarkable progress in communication media and speed, and file compression technology, text-centric data has been shifting to multimedia data such as image and motion picture. So it is currently required that methologies be developed to effectively utilize the related information. With respect to the processing of image data, it is certain that the optimal method should be come up with reflecting the unique characteristics and utilization of image data, apart from the traditional way of processing and storing the legacy text-based data. The study suggests the system of indexing and implementing design image information through the case of analyzing design image data, abstracting data elements of image itself, and finally applying it to building image-oriented database for use.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1236-1243
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• 2003

In this paper, we designed and implemented a practice-oriented simulation-type web courseware to learn the ‘Digital Circuits’ subject effectively. The implemented web courseware utilized multimedia elements such as graphics, animations, and voices etc. for improving understanding and interaction of learning. Also, the web courseware could be easily updated a learning information by using database built in a web server system. In result, the implemented web courseware could encourage a learner with a motive of learning and improve effects of learning. Also, a learner can widely learn because we can add various contents to database according to need. Furthermore, the web courseware could improve understanding for learning by offering feedback on the result.

• Journal of KIISE:Databases
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• v.30 no.2
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• pp.134-144
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• 2003

Spatial relationships among objects are one of the important ingredients for expressing constraints of an image in image or multimedia retrieval systems. In this paper, we propose a unified image retrieval scheme using spatial relationships among objects and their features. The proposed scheme is especially effective in computing similarity between query image and images in the database. Also, objects and their spatial relationships are captured and annotated in XML. It could give better precision and flexibility in retrieving images from database. Finally, we have implemented a prototype system for retrieving images based on proposed technique and showed some of the experiment results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.343-347
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• 2002

In this paper, we can easily update teaming information by using database built in web server system in implementation of a web courseware that a learner can effectively team the 'Digital Circuits' subject. Also, we offered multimedia elements such as graphics, animations, and voices etc. for increasing understanding and interaction of teaming and designed and implemented a simulation-type web courseware of practice-oriented. In result, it can encourage a learner with a motive of learning and increase effects of teaming. Also, a learner can learn various contents because we can add teaming contents to database according to needs. Furthermore, it can improve understanding for teaming by offering feedback on the result. In future, we need to design and implement circuits with more complex and many functions by adding circuit with function that can store.