• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.693-700
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• 2012

The effective extraction of key frames from a video stream is an essential task for summarizing and representing the content of a video. Accordingly, this paper proposes a new and fast method for extracting key frames from a compressed video. In the proposed approach, after the entire video sequence has been segmented into elementary content units, called shots, key frame extraction is performed by first assigning the number of key frames to each shot, and then distributing the key frames over the shot using a probabilistic approach to locate the optimal position of the key frames. The main advantage of the proposed method is that no time-consuming computations are needed for distributing the key frames within the shots and the procedure for key frame extraction is completely automatic. Furthermore, the set of key frames is independent of any subjective thresholds or manually set parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4533-4551
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• 2014

The effective extraction of key frames from a video stream is an essential task for summarizing and representing the content of a video. Accordingly, this paper proposes a new and fast method for extracting key frames from a compressed video. In the proposed approach, after the entire video sequence has been segmented into elementary content units, called shots, key frame extraction is performed by first assigning the number of key frames to each shot, and then distributing the key frames over the shot using a probabilistic approach to locate the optimal position of the key frames. Moreover, we implement our proposed framework in Android to confirm the validity, availability and usefulness. The main advantage of the proposed method is that no time-consuming computations are needed for distributing the key frames within the shots and the procedure for key frame extraction is completely automatic. Furthermore, the set of key frames is independent of any subjective thresholds or manually set parameters.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.3
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• pp.137-143
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• 2003

Key frame extraction has been recognized as one of tile important research issues in video information retrieval. Although progress has been made in key frame extraction, the existing approaches do not evaluate the importance of extracted frame Quantitatively, and Dey are computationally expensive or ineffective. In this Paper, we introduce a new 미해rithm for key frame extraction using shot coverage and distortion. The algorithm finds significant key frames from candidate key frames. When selecting the candidate frames, the coverage rate to the total frames from each frame is computed by using the difference between the adjacent frames in tile shot. The frames within 10$\%$ from the top are selected as the candidates. Then, by comfuting the distortion rate of the candidates against all frames, pick the frames which arc most representative are selected. The performance of the proposed algorithm has been verified by a statistical test. Experiments show that more than 13-50$\%$ improvement has been obtained by the proposed algorithm compared to the existing methods.

• Journal of Ginseng Research
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• v.45 no.1
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• pp.1-21
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• 2021

Panax species have gained numerous attentions because of their various biological effects on cardiovascular, kidney, reproductive diseases known for a long time. Recently, advanced analytical methods including thin layer chromatography, high-performance thin layer chromatography, gas chromatography, high-performance liquid chromatography, ultra-high performance liquid chromatography with tandem ultraviolet, diode array detector, evaporative light scattering detector, and mass detector, two-dimensional high-performance liquid chromatography, high speed counter-current chromatography, high speed centrifugal partition chromatography, micellar electrokinetic chromatography, high-performance anion-exchange chromatography, ambient ionization mass spectrometry, molecularly imprinted polymer, enzyme immunoassay, 1H-NMR, and infrared spectroscopy have been used to identify and evaluate chemical constituents in Panax species. Moreover, Soxhlet extraction, heat reflux extraction, ultrasonic extraction, solid phase extraction, microwave-assisted extraction, pressurized liquid extraction, enzyme-assisted extraction, acceleration solvent extraction, matrix solid phase dispersion extraction, and pulsed electric field are discussed. In this review, a total of 219 articles published from 1980 to 2018 are investigated. Panax species including P. notoginseng, P. quinquefolius, sand P. ginseng in the raw and processed forms from different parts, geographical origins, and growing times are studied. Furthermore, the potential biomarkers are screened through the previous articles. It is expected that the review can provide a fundamental for further studies.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.536-538
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• 2005

As multimedia data and huge-Quantity video data having been increasingly and commonly used, the key frame algorithm, as one of the methods for manipulating these kinds of data, became an important matter and has been studied for many years. But the formerly proposed key frame extraction methods take much processing time or need complex calculations due to decoding processes. In order to solve these problems which the former methods have and to enhance the key frame extraction efficiency, a novel key frame extraction method in compressed domain is proposed in this paper. In this method we get an edge histogram for each I-frame in DCT domain and then extract the key frames by means of histogram difference metric. Experimental results show that our algorithm achieves fast processing speed and high accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2919-2937
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• 2020

Post-Quantum Cryptography (PQC) is rapidly developing as a stable and reliable quantum-resistant form of cryptography, throughout the industry. Similarly to existing cryptography, however, it does not prevent a third-party from using the secret key when third party obtains the secret key by deception, unauthorized sharing, or unauthorized proxying. The most effective alternative to preventing such illegal use is the utilization of biometrics during the generation of the secret key. In this paper, we propose a biometric-based secret key generation scheme for multivariate quadratic signature schemes, such as Rainbow. This prevents the secret key from being used by an unauthorized third party through biometric recognition. It also generates a shorter secret key by applying Principal Component Analysis (PCA)-based Confidence Interval Analysis (CIA) as a feature extraction method. This scheme's optimized implementation performed well at high speeds.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.4
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• pp.595-604
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• 2013

Currently, registered number of imported vehicles is increasing rapidly over the years. Accordingly, environment improvements of vehicle maintenance company for maintenance of luxury vehicle such as imported vehicle are continuously being made. In this paper, we propose a key frame extraction method based on HSV color model for smart vehicle management system implementation to offer for customer reliability of maintenance vehicle. After automatically recognize the license plates of the vehicle using vehicle license plate recognition system when the vehicle come in the car center, we check the repair history and request of the vehicle based on it. We implement mobile services which provide extracted key frame images to the user after extract key frames from vehicle repair video. In addition, we verify the superiority of key frame extraction method by applying a smart vehicle management system. Finally, we convert the RGB color to HSV color to improve the performance of proposed key frame extraction scheme. As a result, we confirmed that our scheme is more excellence about 30% in terms of recall than RGB color model from the performance evaluations.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.55-65
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• 2023

In this paper, we apply KeyBERT(Keyword extraction with Bidirectional Encoder Representations of Transformers) algorithm-driven topic extraction and topic frequency analysis to deep learning and reinforcement learning research to discover the rapidly changing trends in them. First, we crawled abstracts of research papers on deep learning and reinforcement learning, and temporally divided them into two groups. After pre-processing the crawled data, we extracted topics using KeyBERT algorithm, and then analyzed the extracted topics in terms of topic occurrence frequency. This analysis reveals that there are distinct trends in research work of all analyzed algorithms and applications, and we can clearly tell which topics are gaining more interest. The analysis also proves the effectiveness of the utilized topic extraction and topic frequency analysis in research trend analysis, and this trend analysis scheme is expected to be used for research trend analysis in other research fields. In addition, the analysis can provide insight into how deep learning will evolve in the near future, and provide guidance for select research topics and methodologies by informing researchers of research topics and methodologies which are recently attracting attention.

• Journal of the Korea Computer Graphics Society
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• v.29 no.1
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• pp.1-11
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• 2023

Deep-learning-based image segmentation is one of the most widely employed lane detection approaches, and it requires a post-process for extracting the key points on the lanes. A general approach for key-point extraction is using a fixed threshold defined by a user. However, finding the best threshold is a manual process requiring much effort, and the best one can differ depending on the target data set (or an image). We propose a novel key-point extraction algorithm that automatically adapts to the target image without any manual threshold setting. In our adaptive key-point extraction algorithm, we propose a line-level normalization method to distinguish the lane region from the background clearly. Then, we extract a representative key point for each lane at a line (row of an image) using a kernel density estimation. To check the benefits of our approach, we applied our method to two lane-detection data sets, including TuSimple and CULane. As a result, our method achieved up to 1.80%p and 17.27% better results than using a fixed threshold in the perspectives of accuracy and distance error between the ground truth key-point and the predicted point.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.179-182
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• 2001

In this paper. a key frame extraction algorithm for browsing and searching the summary of a video is proposed. Toward this end, important frames representing a shot are selected according to the correlations among frames. by using the Fourier descriptor which is useful for the shot boundary detection. To quantitatively evaluate the importance of selected frames. a new measure based on correlation coefficients of frames is proposed. If there are several frames with a same importance. another criteria is introduced to break the tie. by computing the partial moment of subframes including each candidate key frame so that the distortion rate is minimized Since a key frame extraction algorithm can be evaluated subjectively. the performance of the proposed algorithm has been verified by a statistical test. Experiments show that more than 20% improvement has been obtained by the proposed algorithm compared to existing methods.