• Journal of the Korea Computer Industry Society
• /
• v.3 no.7
• /
• pp.927-936
• /
• 2002

This paper presents the extraction of a feature by motion vector for efficient content-based retrieval for digital video. in this paper, divided by general size block for the current frame by video, using BMA(block matching algorithm) for an estimate by block move based on a time frame. but in case BMA appeared on a different pattern fact of motion in the vector obtain for the BMA. solve in this a problem to application for full search method this method is detected by of on many calculations. I propose an alternative plan in this paper Limit the search region to $\pm$15 and search is a limit integer pixel. a result, in this paper is make an estimate motion vector in more accurately using motion vector in adjoin in blocks. however, refer to the block vector because occurrence synchronism. Such addition information is get hold burden receive to transmit therefore, forecasted that motion feature each block and consider for problems for establish search region. in this paper Algorithm based to an examination Motion Estimation method by for motion Compensation is proposed.

• Journal of KIISE:Software and Applications
• /
• v.34 no.1
• /
• pp.59-69
• /
• 2007

In the video with a various environment, background modeling is important for extraction and recognition the moving object. For this object recognition, many methods of the background modeling are proposed in a process of preprocess. Among these there is a Kumar method which represents the Queue-based background modeling. Because this has a fixed period of updating examination of the frame, there is a limit for various system. This paper use a background modeling based on the queue. We propose the method that major parameters are decided as adaptive by background model. They are the queue size of the sliding window, the sire of grouping by the brightness of the visual and the period of updating examination of the frame. In order to determine the factors, in every process, RCO (Ratio of Correct Object), REO (Ratio of Error Object) and UR (Update Ratio) are considered to be the standard of evaluation. The proposed method can improve the existing techniques of the background modeling which is unfit for the real-time processing and recognize the object more efficient.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 1999.11a
• /
• pp.224-229
• /
• 1999

In the field of speech recognition, the research area can be classified into the following two categories: one which is concerned with the development of phoneme-level recognition system, the other with the efficiency of word-level recognition system. The resonable phoneme-level recognition system should detect the phonemic boundaries appropriately and have the improved recognition abilities all the more. The traditional LPC methods detect the phoneme boundaries using Itakura-Saito method which measures the distance between LPC of the standard phoneme data and that of the target speech frame. The MFCC methods which treat spectral transitions as the phonemic boundaries show the lack of adaptability. In this paper, we present new speech recognition system which uses auto-correlation method in the phonemic boundary detection process and the multi-layered Feed-Forward neural network in the recognition process respectively. The proposed system outperforms the traditional methods in the sense of adaptability and another advantage of the proposed system is that feature-extraction part is independent of the recognition process. The results show that frame-unit phonemic recognition system should be possibly implemented.

• Journal of the Institute of Convergence Signal Processing
• /
• v.5 no.3
• /
• pp.230-235
• /
• 2004

This paper describes FPGA implementation of a pointer interpreter which can support a synchronization of SDH(or SONET)-based transmission network. The pointer interpreter consists of a pointer-word extractor and a pointer-word interpreter The pointer-word extractor which is composed of mod-6480 counter, shift register and pointer synchronizing block, finds out the H1 and H2 pointer word from a 51.84 Mb/s AU-3/STS-1 data frame and then performs the synchronizing with a 6.48 Mb/s by dividing them in 8. Based on the extracted pointer word, pointer-word interpreter analyzes pointer states such LOP, AIS and NORM according to pointer state-transition algorithm. It consists of a majority vote, a pointer word valid/invalid check, a pointer justification, and a pointer state check. The simulation results of Xilinx Virtex XCV200PQ240 FPGA chip shows the exact pointer word extraction and correct decision of pointer status based on extracted pointer word. The proposed pointer interpreter is suitable for pointer interpretation of 155 Mb/s STM-1/STS-3 frame.

• The Journal of the Acoustical Society of Korea
• /
• v.27 no.4
• /
• pp.200-206
• /
• 2008

This paper presents a method of quantization to extract quantization parameters using the straight-line and DCT (Discrete Cosine Transform) for two splited frequency bands. As the number of harmonic is variable frame to frame, harmonics in low frequency band is oversampled to fix the dimension and straight-lines present a spectral envelope, then the discontinuous points of straight-lines in low frequency is sent to quantizer. Thus, extraction of quantization parameters using the straight-line provides a fixed dimension. Harmonics in high frequency use variable DCT to obtain quantization parameters and this paper proposes a method of quantization combining the straight-line with DCT. The measurement (If proposed method of quantization uses spectral distortion (SD) for spectral magnitudes. As a result, The proposed method of quantization improved 0.3dB in term of SD better than HVXC.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.39 no.3
• /
• pp.66-77
• /
• 2002

This paper deals with an implementation of the navigation parameter extraction technique using the TMS320C80 multimedia video processor (MVP). Especially, this Paper focuses on the relative position estimation algorithm which plays an important role in real-time operation of the overall system. Based on the relative position estimation algorithm using the images obtained at two locations, we develop a fast algorithm that can reduce large amount of computation time and fit into fixed-point processors. Then, the algorithm is reconfigured for parallel processing using the 4 parallel processors in the MVP. As a result, we shall demonstrate that the navigation parameter extraction system employing the MVP can operate at full-frame rate, satisfying real-time requirement of the overall system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.23 no.3
• /
• pp.313-322
• /
• 2005

Rapid advances in technology and changes in human and cultural activities bring about changes to the earth surface in terms of spatial extension as well as time frame of the changes. Such advances introduce shorter updating frequency of maps and geospatial database. To satisfy these requirements, recent research efforts in the geoinformatics field have been focused on the automation and speeding up of the mapping processes which resulted in products such as the digital photogrammetric workstation, GPSIINS, applications of satellite imagery, automatic feature extraction and the LiDAR system. The possibility of automatically extracting buildings and generating contours from airborne LiDAR data has received much attention because LiDAR data produce promising results. However, compared with the manually derived building footprints using traditional photogrammetric process, more investigation and analysis need to be carried out in terms of accuracy and efficiency. On the other hand, generation of the contours with LiDAR data is more efficient and economical in terms of the quality and accuracy. In this study, the effects of various conditions of the pre-processing phase and the subsequent building extraction and contour generation phases for digital mapping have on the accuracy were investigated.

• Journal of the Korea Convergence Society
• /
• v.8 no.5
• /
• pp.13-17
• /
• 2017

Existing Speech feature extracting method in speech Signal, there are incorrect recognition rates due to incorrect speech which is not clear threshold value. In this article, the modeling method for improving speech recognition performance that combines the feature extraction for speech and silence characteristics normalized to the non-speech. The proposed method is minimized the noise affect, and speech recognition model are convergence of speech signal feature extraction to each speech frame and the silence feature normalization. Also, this method create the original speech signal with energy spectrum similar to entropy, therefore speech noise effects are to receive less of the noise. the performance values are improved in signal to noise ration by the silence feature normalization. We fixed speech and non speech classification standard value in cepstrum For th Performance analysis of the method presented in this paper is showed by comparing the results with CHMM HMM, the recognition rate was improved 2.7%p in the speech dependent and advanced 0.7%p in the speech independent.

• Journal of Broadcast Engineering
• /
• v.18 no.4
• /
• pp.559-571
• /
• 2013

This paper has presented a few problems when the 2D video superimposed the overlay text was converted to the 3D stereoscopic video. To resolve the problems, it proposes the scenario which the original video is divided into two parts, one is the video only with overlay text graphic region and the other is the video with holes, and then processed respectively. And this paper focuses on research only to detect and extract the overlay text graphic region, which is a first step among the processes in the proposed scenario. To decide whether the overlay text is included or not within a frame, it is used the corner density map based on the Harris corner detector. Following that, the overlay text region is extracted using the hybrid method of color and motion information of the overlay text region. The experiment shows the results of the overlay text region detection and extraction process in a few genre video sequence.

• Journal of Korea Multimedia Society
• /
• v.9 no.11
• /
• pp.1465-1473
• /
• 2006

In this paper, we present an approach for facial expression recognition using Active Shape Models(ASM) and a state-based model in image sequences. Given an image frame, we use ASM to obtain the shape parameter vector of the model while we locate facial feature points. Then, we can obtain the shape parameter vector set for all the frames of an image sequence. This vector set is converted into a state vector which is one of the three states by the state-based model. In the classification step, we use the k-NN with the proposed similarity measure that is motivated on the observation that the variation-regions of an expression sequence are different from those of other expression sequences. In the experiment with the public database KCFD, we demonstrate that the proposed measure slightly outperforms the binary measure in which the recognition performance of the k-NN with the proposed measure and the existing binary measure show 89.1% and 86.2% respectively when k is 1.