• Proceedings of the IEEK Conference
• /
• 2002.06d
• /
• pp.93-96
• /
• 2002

This paper presents robust and efficient scene-based video watermarking method using visual rhythm (spatio-temporal slice) in compressed domain. Scene change can be detected easily using visual rhythm and video sequences are conveniently edited at the scene boundaries. Therefore, scene-based watermark embedding Process it a natural choice. Temporal spread spectrum can be achieved by applying spread spectrum methods to visual rhythm. Additive Gaussian noise, low-pass filtering, median filtering and histogram equalization attack are simulated for all frames. Frame sub-sampling is also simulated as a typical video attack Simulation results show that proposed algorithm is robust and efficient in the presence of such kind of attacks.

• The Journal of the Korea Contents Association
• /
• v.7 no.10
• /
• pp.27-35
• /
• 2007

Radio Frequency Identification(RFID) technology is set to play an essential role in object tracking or supply chain management systems. New challenges for RFID data management are needed in the RFID applications. RFID data are generated quickly and automatically, and can be used for object tracking, or for real-time monitoring. These applications are mostly associated with the timestamps when the events happen. In this paper, we propose a temporal RFID data model to maintain the history of events and state changes and to monitor the states of RFID objects. Also we propose data filtering method of non active data based on temporal RFID data model. This data model involves essential basic operations for RFID data. We show increased query performance through the data filtering method of non active data.

• The KIPS Transactions:PartD
• /
• v.11D no.4
• /
• pp.835-844
• /
• 2004

Recently, the location-based service for moving customers is becoming one of the most important service in mobile communication area. For moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. Range queries, whose range can be window or circular, are the most essential query types in LBS. We need to distinguish completely contained cells from partially contained cells in those range queries. Also, it is necessary to consider temporal dimension to filter out qualifying objects correctly. In this paper, we adopt two-level index structures with fixed grid file structures in the second level, which are designed to minimize update operations. We propose a spatial ceil filtering method using VP filtering and a combined spatio-temporal filtering method using time gone concepts. Some experimental results are shown for various window queries and circular queries with different filtering combinations to show the performance tradeoffs of the proposed methods.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.5
• /
• pp.526-529
• /
• 2003

Recommender systems or collaborative filtering are methods to identify potentially interesting or valuable items to a particular user Under the assumption that people with similar interest tend to like the similar types of items, these methods use a database on the preference of a set of users and predict the rating on the items that the user has not rated. Usually the preference of a particular user is liable to vary with time and this temporal variation may cause an inaccurate identification and prediction. In this paper we propose a method to adapt the temporal variation of the user preference in order to improve the predictive performance of a collaborative filtering algorithm. To be more specific, the correlation weight of the GroupLens system which is a general formulation of statistical collaborative filtering algorithm is modified to reflect only recent similarity between two user. The proposed method is evaluated for EachMovie dataset and shows much better prediction results compared with GrouPLens system.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.10C
• /
• pp.1023-1032
• /
• 2003

Object-based coding, such as MPEG-4, enables various content-based functionalities for multimedia applications. In order to support such functionalities, as well as to improve coding efficiency, each frame of video sequences should be segmented into video objects. In this paper. we propose an effective video object segmentation method using nonlinear multiscale filtering and spatio-temporal information. Proposed method performs a spatial segmentation using a nonlinear multiscale filtering based on the stabilized inverse diffusion equation(SIDE). And, the segmented regions are merged using region adjacency graph(RAG). In this paper, we use a statistical significance test and a time-variant memory as temporal segmentation methods. By combining of extracted spatial and temporal segmentations, we can segment the video objects effectively. Proposed method is more robust to noise than the existing watershed algorithm. Experimental result shows that the proposed method improves a boundary accuracy ratio by 43% on "Akiyo" and by 29% on "Claire" than A. Neri's Method does.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.4
• /
• pp.706-713
• /
• 1997

In this paper, we propose a band stop filter(BSF) for reducing drag-like effect of the low pass filter(LPF), a block by block adaptive filtering method, and a motion adaptive filtering method, which show better results in terms of PSNR or human visual perception compared to the conventional method using LPF. The BSF improves the draglike effects of the low pass filter by passing temporal high frequency components of video sequences which correspond to objects with large motion. The proposed adaptive methods also improve the conventional adaptive filtering by modifying the conventional algorithm and applying the algorithms for small blocks. The simulation results show that the proposed filtering methods show better results in terms of PSNR and subjective tests in most cases. Also in case of block by block adaptive filtering, it is verified that the application of the algorithm for smaller block gives better results.

• Proceedings of the IEEK Conference
• /
• 2005.11a
• /
• pp.335-338
• /
• 2005

In this paper, we proposed a new MCTF (Motion Compensated Temporal Filtering) technique and its hardware (H/W) architecture for SVC (Scalable Video Coding). Since the proposed MCTF Kernel has a extensible architecture, it executes temporal filtering using (5,3) and (3,1) lifting operation. Also it has the same output data rate as the input, and it can continuously produce filtered frames after some latency time. Since the proposed architecture has simpler architecture than previous ones, it is easily mapped into H/W and has optimized memory usage rate and low cost.

• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.433-436
• /
• 2003

In this paper, the efficient motion estimation and compensation method for 3 dimensional wavelet transform is proposed. Recently, since the compression performance and scalable functionality are provided by wavelet transform, many researches have been carried out for applying to the video compression. For the temporal filtering, motion estimation and compensation techniques are used, but the unconnected pixels, which are produced by motion compensation result into the degradation of coding performance and quality of the picture. For the efficient motion compensated temporal filtering by reducing the number of these unconnected pixels, we propose the variable block size motion estimation and compensation method. Also we propose a method that determines the block size using rate-distortion optimization technique according to the local characteristics of the frame. The simulation results show the improved performances than the MPEG-4 scalable coding methods and the 3 dimensional wavelet coding methods using fixed block size motion estimation and compensation.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.12
• /
• pp.1346-1351
• /
• 2014

We propose a novel approach for stereophonic acoustic echo suppression using spectro-temporal filtering based on soft decision. Unlike the conventional approaches estimating the echo pathes directly, the proposed technique can estimate stereo echo spectra without any double-talk detector. In order to improve the estimation of echo spectra, the extended power spectrum density matrix and echo overestimation control matrix are applied on this method. In addition, this echo suppression technique is based on soft decision technique using speech absence probability in STFT domain. Experimental results show that the proposed method improves compared with the conventional approaches.

• Journal of KIISE:Databases
• /
• v.36 no.4
• /
• pp.280-291
• /
• 2009

Skyline Query processing is important to wireless sensor applications in order to process multi-dimensional data efficiently. Most skyline researches about sensor network focus on minimizing the energy consumption due to the battery powered constraints. In order to reduce energy consumption, Filtering Method is proposed. Most existing researches have assumed a snapshot skyline query processing and do not consider continuous queries and use data generated in ancestor node. In this paper, we propose an energy efficient method called Bottom up filtering tuple selection for continuous skyline query processing. Past skyline data generated in child nodes are stored in each sensor node and is used when choosing filtering tuple. We also extend the algorithms, called Support filtering tuple(SFT) that is used when we choose the additional filtering tuple. There is a temporal correlation between previous sensing data and recent sensing data. Thus, Based on past data, we estimate current data. By considering this point, we reduce the unnecessary communication cost. The experimental results show that our method outperforms the existing methods in terms of both data reduction rate(DRR) and total communication cost.