There are many Problems such as low detection ratio, velocity and increase of false hit ratio on the detection of gradual scene changes with the previous shot transition detection algorithms. In this paper, we Propose an improved dissolve detection method using color information on low-frequency subband and edge elements on high-frequency subband. The Possible dissolve transition are found by analyzing the edge change ratio in the high-frequency subband with edge elements of each direction. Using the double chromatic difference on the lowest frequency subband, we have the improvement of the dissolve detection ratio. The simulation results show that the performance of the proposed algorithm is better than the conventional one for dissolve detection on a diverse set of uncompressed video sequences.

We present an image retrieval method that improves retrieval rate by using the fusion of histogram and wavelet moment features. The key idea is that images similar to a query image are selected in DB by using the wavelet moment features. Then the result images are retrieved from the selected images by using histogram method. In order to evaluate the performance of the proposed method, we use Brodatz texture database, MPEG-7 T1 database and Corel Draw photo. Experimental result shows that the proposed method is better than each of histogram method and wavelet moment method.

In this paper, we propose a method for text extraction in the Web images. Our approach is based on contrast detecting and pixel component ratio analysis in mouse position. Extracted data with OCR can be used for real time dictionary call or language translation application in Web browser.

In this paper, we present a new multiple description embedded zerotree wavelet coding method using the two splitted thresholds. We first model a half EZW coder and then we present multiple description coder which has two coding channels using wide threshold EZW(WTEZW) coders. To evaluate the performance of the proposed coder, we provide an image coding applications with two descriptions and compare MDC image coding results reported to date.

본 논문에서는 정확한 비트 제어가 가능한 I-frame의 효율적인 부호화 방법을 제안한다. 기존 H.263＋의 DCT 계수들을 트리 구조로 재구성하여 각 계수에 대해 임베이드 제로트리 부호화 알고리즘을 적용시켜 부호화함으로써 코딩 효율을 향상시킴과 동시에 비트 율의 제어가 용이하도록 한다. 제안 방법의 유효성을 검증하기 위해 표준 동영상에 대한 컴퓨터 모의 실험 결과 제안 방법은 기존의 부호화 방법에 비해 비트 제어가 용이하고 부호화 성능이 개선됨을 확인했다.

In this paper, we propose new method for denoising in processing the image compression. Usually, to compress the noise image, we must have the denoising step before encoding. But this method has a embedded character, so need not an additional noise eliminator. In SAQ step, an embedded signal is quantized more detail and the other side is suppressed. Comparing with the conventional method, we can get the enhanced image quality.

In this paper, we proposed multispectral image compression method using CIP (classified inter-channel prediction) and SVQ (selective vector quantization) in wavelet domain. First, multispectral image is wavelet transformed and classified into one of three classes considering reflection characteristics of the subband with the lowest resolution. Then, for a reference channel which has the highest correlation with other channels, the variable VQ is performed in the classified intra-channel to remove spatial redundancy. For other channels, the CIP is performed to remove spectral redundancy. Finally, the prediction error is reduced by performing SVQ. Experiments are carried out on a multispectral image. The results show that the proposed method reduce the bit rate at higher reconstructed image quality and improve the compression efficiency compared to conventional method.

The method of Content-based Triangular Mesh Image representation in moving pictures makes better performance in prediction error ratio and visual efficiency than that of classical block matching. Specially if background and objects can be separated from image, the objects are designed by Irregular mesh. In this case this irregular mesh design has an advantage of increasing video coding efficiency. This paper presents the techniques of mesh generation, motion estimation using these mesh, uses image warping transform such as Affine transform for image reconstruction, and evaluates the content based mesh design through computer simulation.

Motion estimation plays an important role for video coding. In this paper, we derive optimal search patterns for fast block matching motion estimation. By analyzing the block matching algorithm as a function of block shape and size, we can find an optimal search pattern for initial motion estimation. The proposed idea, which has been verified experimentally by computer simulations, can provide an analytical basis for the current MPEG-2 proposals. In order to choose a more compact search pattern for BMA, we exploit the statistical relationship between the motion and the frame difference of each block.

In this paper, we propose a fast adaptive diamond search algorithm(FADS) for block matching motion estimation. Fast motion estimation algorithms reduce the computational complexity by using the UESA (Unimodal Error Search Assumption) that the matching error monotonically increases as the search moves away from the global minimum error. Recently many fast BMAs(Block Matching Algorithms) make use of the fact that the global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the adjacent blocks. We change the origin of search window according to the spatially adjacent motion vectors and their MAE(Mean Absolute Error). The computer simulation shows that the proposed algorithm has almost the same computational complexity with UCBDS(Unrestricted Center-Biased Diamond Search)〔1〕, but enhance PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS(Full Search), even for the large motion case, with half the computational load.

In this paper we propose the multiple local search method(MLSM) based on the motion information of the neighbor blocks. In the proposed method motions are estimated from the multiple searches of many candidate local search regions. To reduce the additional search points we avoid to search the same candidate regions previously visited using the distance from the initial search point to the recently found vector points. In the simulation the proposed method shows more excellent results than that of other gradient based method especially in the search of motion boundary.

In this work, the new algorithm that automatically extracts moving object of the video image is presented. In order to extract moving object, it is that velocity vectors correspond to each frame of the video image. Using the estimated velocity vector, the position of the object are determined. the value of the coordination of the object is initialized to the seed, and in the image plane, the moving object is automatically segmented by the region growing method. As the result of an application in sequential images, it is available to extract a moving object.

In this paper, we propose a new interpolation method by using the motion between two moving image frames. In the proposed method, the movement is detected by using neighborhood pixels of target pixel in the past frame and the present frame. Then, H-shaped pseudomedian filter (below HPMED) is used for the still part of the image and Delta-shaped interpolation filter (below $\Delta$-shaped) for used in the moving part of the image. We detect the movement by comparing the differences between pixels in 4${\times}$5 window of the past frame and the present frame; the difference has a critical value. We simultaneously accomplish checking PSNR(peak signal noise ratio) and subjective assessment that is placed the focus on edge characteristic for assessment of result in computer simulation. The results show that the proposed adaptive method is better than the conventional methods.

In this paper, we propose a new performance comparison method of various Interpolation methods for image enlargement The conventional methods employs PSNR and edge characteristic evaluation for performance comparison of interpolation methods. The proposed performance comparison method uses the position Information for each difference pixel's value and the frequency characteristic information between original image and Interpolated image. The proposed methods might be useful for performance comparison of various Interpolation methods through the computer simulation.

In order to reconstruct a high resolution image, it is important to reconstruct frames from fields. A number of approaches have been developed in making frames. In this paper, we propose a new deinterlacing algorithm based on local motion compensation, which is performed based on statistical property. The proposed algorithm achieves faster processing speed than block matching algorithm and higher resolution than inter-field interpolation. The effectiveness of the proposed algorithm is demonstrated experimentally.

In this paper, we proposed a postprocessing algorithm for quantization effects reduction in block coded images using the block classification and adaptive filtering. The proposed method consists of classification, adaptive inter-block filtering, and intra-block filtering. First, each block is classified into one of seven classes based on the characteristics of 8${\times}$8 DCT coefficients. Then each block boundary is filtered by adaptive inter-block filters according to the block classification. Finally for blocks which are classified into edge block, intra-block filtering is peformed. Experimental results show that the proposed method gives better results than the conventional methods from both a subjective and an objective viewpoint.

The error diffusion is good for reproducing continuous image to binary image. However the reproduction of edge characteristics is weak in power spectrum analysis of display error. It is suggested for us an edge-enhanced error-diffusion method that is included pre-processing algorithm for edge characteristic enhancement. Pre-processing algorithm is organized horizontal and vertical directional 2nd order differential values and weighting function of pre-filter. The improved Error diffusion using pre-filter, presents a good results visually which edge characteristics is enhanced. The performance of the proposed algorithm is compared with that of the conventional edge-enhanced error diffusion by measuring the RAPSD of display error, the egde correlation and the local average accordance.

In this paper, the speaker-recognition process based on both DTW and discrete HMM was performed using the method to evaluate state-dependent parameter weighting from training data so as the personal audio-characteristics are to be well reflected. In the suggested method below, we found the optimal state sequence using the Viterbi algorithm. The optimal path could be evaluated after comparing the sequence of base pattern which already have, with that of the other patterns. After that the frame of which the pattern was matched with the base pattern in the same state are to be found so that the reference pattern can be gained by weighting on the numbers of matched frames.

In this paper, a new technology for extracting the feature of the speech signal of an isolated word by the analysis on the frequency domain is proposed. This technology can be applied efficiently for the limited speech domain. In order to extract the feature of speech signal, the number of peaks is calculated and the value of the frequency for a peak is used. Then the difference between the maximum peak and the second peak is also considered to identify the meanings among the words in the limited domain. By implementing this process hierarchically, the feature of speech signal can be extracted more quickly.

In pattern classification, the Bhattacharyya distance has been used as a class separability measure and provides useful information for feature selection and extraction. In this paper, we propose a method to predict the classification error for multimodal data based on the Bhattacharyya distance. In our approach, we first approximate the pdf of multimodal distribution with a Gaussian mixture model and find the bhattacharyya distance and classification error. Exprimental results showed that there is a strong relationship between the Bhattacharyya distance and the classification error for multimodal data.

개인용 컴퓨터가 멀티미디어 환경으로 변함에 따라서 인식률 향상과 처리시간 단축을 요구하고 있다. 본 논문은 기준패턴의 수가 증가함에 따라 발생하는 처리시간 증가 문제의 해결과 인식률 향상에 관한 것이다. 기준패턴의 수를 줄이기 위한 방법으로 각 모음별 포만트 정보를 구한 뒤 시험패턴과 비교할 후보자를 미리 정하여 인식률을 향상시키는 방법을 제안하고자 한다. 위와 같은 방법으로 모의 실험한 결과 전체 시스템 인식률이 기존의 방법에 비하여 0.5% 정도 향상되었고, 처리시간은 10%정도 감소하였다.

An AMR(Adaptive Multi-Rate) speech coding algorithm has been adopted as a standard speech codec for IMT-2000. It is based on the algebraic CELP, and consists of eight speech coding modes having the bit rate from 4.75 kbit/s to 12.2 kbit/s. It also contains the VAD(Voice Activity Detector), SCR (Source Controlled Rate) operation, and error concealment scheme for robustness in a radio channel. The bit rate of AMR is changed on a frame basis depending on the channel condition. In this paper, we introduced AMR speech coding algorithm and performed the real-time implementation using TMS320C6201, i.e., a Texas Instrument's fixed-point DSP. With the ANSI C source code released from ETSI and 3GPP, we convert and optimize the program to make it run in real time using the C compiler and assembly language. It is verified that the decoded result of the implemented speech codec on the DSP is identical with the PC simulation result using ANSI C code for test sequences. Also, actual sound input/output test using microphone and speaker demonstrates its proper real-time operation without distortions or delays.

On CELP type Vocoders G.723.1 6.3kbps/5.3kbps Dual Rate Speech Codec, which is developed for Internet Phone and videoconferencing, uses VAD(Voice Activity Detection)/CNG (Comfort Noise Generator) in order to reduce the bit rate in a silence period. In order to reduce the bit rate effectively in this paper, we first set the boundary condition of the energy threshold to prevent the consumption of unnecessary processing time, and use three decision rules to detect an active frame by energy, pitch gain and LSP distance. To evaluate the performance of the proposed algorithm we use silence-inserted speech data with 0, 5, 10, 20dB of SNR. As a result when SNR is over 5dB, the bit rate is reduced up to about 40% without speech degradation and the processing time is additionally decreased.

This paper propose new sound localization algorithm that calculates TDOA(Time Difference Of Arrival) between the two received signals via two microphone array, The proposed Subband CPSP is a development of Previous CPSP method using subband approach. It first split the received microphone signals into three frequency bands and then calculates subband CPSP with corresponding SNR weights. This type of algorithm, Subband CPSP, can provide more accurate TDOA estimation results because it limits the effects of environmental noise within each subband. To verify the performance of the proposed Subband CPSP algorithm, computer simulation was conducted and it was compared with previous CPSP method. From the both simulation results, the proposed Subband CPSP is superior to previous CPSP algorithm more than accuracy for TDOA estimation.

There have been proposed two types of low bit rate vocoder upto now : One is MBE type using the spectrum modeling and another is CELP type using the hybrid coding method. CELP type vocoder has mainly studied between them. Specially, much of intensity is concentrated in CELP vocoder due to the emergence of Internet Phone and PCS in a domestic. In order to improve the speech quality in CELP vocoder, in this paper, we proposed a new spectrum analysis algorithm with variable window, In CELP vocoder, the spectrum of the synthesised speech signal is distorted because the fixed size windows is used for spectrum analysis. So we have measured the spectral leakage and in order to minimize the spectral leakage have adjusted the window size. Applying this method G.723.1 ACELP, we can get SD(Spectral Distortion) reduction 0.084(dB), residual energy reduction 6.3% and MOS(Mean Opinion Score) improvement 0.1.

In this paper, we consider the problem of digital audio watermarking to robust about compression without original audio data. We specifically address the audio watermarking using BPSK with variable carrier frequency. This technique make audio data embeded watermarking robust with compression attack, for example MPEG, AC-3, etc.

In this paper, we proposed robust digital image watermarking based on modulation transfer function (MTF) of human visual system (HVS). Using the proposed method, robust watermarking is possible both in common image processing operations such as cropping and lossy compression and in geometrical transforms such as rotation, scaling, and translation, because it can embed watermark and template signal maximally using MTF of HVS. Experimental results show that the proposed watermarking method is more robust to several common image processing operations and geometrical transforms.

Nowadays, it is popular to use the spread spectrum watermarking algorithm for still image. But there is high error probability of the retrieved watermark in the spread spectrum owing to the correlation between image and spreaded watermark sequence. In this paper, two methods are proposed. One is Ordering Map Method and the other is Alteration of Image. Based on pixel value, the order by which the spreaded watermark bits is embedded is created in Ordering Map Method. By the covariance function between image and the spreaded sequence, image is altered in Alteration of Image. Hence, bit error of retrieved watermark is clearly reduced to zero by this two method.

In this paper, we propose new watermarking technique using weighting factor decision method in the watermark embedding step and adaptive threshold decision method in the watermark extracting step. In our method, we are determined weighting factor in simple by calculating distance between pixel coefficient and neighborhood pixel coefficients and threshold is adaptively determined by searching the minimized extract error value using histogram of difference value.

In this paper, we explore the possibility to use wavelet decomposition based on modified octave structured 5-level filter banks as a set of features for speech recognition. The HMM (Hidden Markov Model) is used as a recognizer 〔l〕. We compared the performance of the wavelet decomposition with the mel-cepstrum and LPC cepstrum. Experimental results show favorable results.

흉부 X선 CT 화상을 이용한 폐종류의 경계 형상을 정량적으로 평가하기 위하여 푸리에 변환된 폐종류 음영의 윤곽선 내 power spectrum 고주파 성분의 총합이 폐종류 음영의 경계 형상에 관한 유효한 평가 값이 되는지의 여부를 검토하였다. 이 평가 값은 폐종류 음영의 CT 화상 위의 특징을 명확히 반영한다고 판단된다. 다시 말해서, 윤곽선은 양성 혹은 악성 종류에 있어서 각각 명확하거나 불투명하다. 양성 IS명과 악성 16명인 환자 31명에 대해서 이 평가 값을 계산하여 통계적 처리를 행한 결과 양성과 악성 간에 뚜렷한 차이를 인식할 수 있었다. 이러한 제안된 평가 방법에 의해, power spectrum 고주파 성분의 총합이 폐종류 경계 형상의 평가치가 되어, 정량적인 폐종류의 양성과 악성 감별을 행할 때 유용한 값이 될 가능성을 시사한다고 볼 수 있다.

$\mu$BGA(Ball Grid Array) is growing in response to a great demand for smaller and lighter packages for the use in laptop, mobile phones and other evolving products. However it is not easy to find its defect by human visual due to in very small dimension. From this point of view, we are interested its development of a vision based automated inspection algorithm. For this, first a 2D view of $\mu$BGA is described under a special blue illumination. Second, a notation-invariant 2D inspection algorithm is developed. Finally a 3D inspection algorithm is proposed for the case of stereo vision system. As a simulation result, it is shown that 3D defect not easy to find by 2D algorithm can be detected by the proposed inspection algorithm.

Motion Estimation/compensation(ME/MC) is one of the efficient interframe ceding techniques for its ability to reduce the high redundancy between successive frames of an image sequence. Calculating the blocking matching takes most of the encoding time. In this paper a new fast block matching algorithm(BMA) is developed for motion estimation and for reduction of the computation time to search motion vectors. The feature of the new algorithm comes from the center-biased checking concept and the trend of pixel movements. At first, Motion Vector(MV) is searched in ${\pm}$1 of search area and then the motion estimation is exploited in the rest block. The ASP and MSE of the proposed search algorithm show good performance.

Hausdorff distance(HD) commonly used measures for object matching, and calculates the distance between two point set of pixels in two-dimentional binary images without establishing correspondence. And it is realized as the image filter applying the fuzzy. In this paper, the fuzzy hardware realizes in order to construct the image filter applying HD, also, propose as the method for the noise removal using it in the image. MIN-MAX circuit designs the circuit using MAX-PLUS, and the fuzzy HD hardware results are obtained to the simulation. And then, the previous computer simulation is confirmed to the result by using MATLAB.

Standard of implementing a robot is Man, so in many field, Many studies are processing to archive a robot, very similar to human being. This paper, based on the theory of man, implemented on the model of parallelism sense and visual information, which is needed when it's moving. Introduced robot uses CCD and designed Image Processing Board for the purpose of archiving vision data. To keep parallel condition, This use ultrasonic sensors for auto-mobile.

In this paper, we propose a Windows-based presentation system using laser pointer mouse. Major-characteristics of this system is to synchronize the laser pointing position with the PC cursor such that the laser can function as not only pointer, but also a PC mouse. It is shown that we use a special pattern to coincide the coordinate of the camera capture image with that of the pc window. We finally show its feasibility by some experiments with the implemented system.

Selecting locally optimum thresholds, based on optimizing a criterion composed of the area variation rate and the compactness of the segmented shape, is presented. The method is shown to have the shape-resolving property in the subtraction image, so that overlapped objects may be resolved into bright and dark evidences characterizing each object. As an application a vehicle detection algorithm robust to the operating conditions could be realized by applying simple merging rules to the geometrically correlated bright and dark evidences obtained by this local thresholding.

Real-time traffic detection scheme based on Computer Vision is capable of efficient traffic control using automatically computed traffic information and obstacle detection in moving automobiles. Traffic information is extracted by segmenting vehicle region from road images, in traffic detection system. In this paper, we propose the advanced segmentation of vehicle from road images using multiple local region information. Because multiple local region overlapped in the same lane is processed sequentially from small, the traffic detection error can be corrected.

In this paper, we propose the edge compensation algorithm which connects the adjacent edges without losing the information of the skeletons on the edge image. The proposed edge compensation algorithm is composed of succeeding two steps. In the first step, the uplifted image is obtained by applying the uplifting process to the edge image. The next step is to extract the edge image from the uplifted image using the skeleton extraction algorithm. Experimental results show that the proposed method connects the adjacent edges without the distortion of the original edge information compared to the traditional method

In this paper, we present a new interpolation method for the color filter away(CFA). In order to capture color images. typical input devices use a single chip CCD imaging sensor with color filter array. As a result, the single chip CCD does not provide sufficient color resolutions since it arranges different color filters sequentially on a single CCD, resulting in aliasing noise and loss of resolution. In order to reconstruct high quality color images, we propose to use the interpolation algorithm using high order B-splines. Experiments show promising results.

본 논문에서는 높은 압축률과 고음질을 제공하는 MPEG-1 Layer Ⅲ 오디오 디코더를 고정소수점 DSP인 TMS320C6201을 이용하여 실시간으로 동작하도록 구현하였다. ISO/IEC에서 제공하는 부동소수점 C 프로그램을 음질의 손실 없이 고정소수점 연산으로 변환하었고 실시간 동작을 위하여 최적화 작업을 수행하였다. 연산의 정확성을 높이기 위해서 Descaling 모듈에 중점을 두어 부동소수점 연산을 고정소수점 연산으로 변환하였고 IMDCT 모듈과 Synthesis Polyphase Filter Bank 모듈에 대해 고속 알고리즘을 적용하여 연산량과 프로그램 크기를 크게 줄일 수 있었다. 구현된 디코더는 TMS320C6201 DSP가 수행할 수 있는 최대 연산량의 26%만으로 실시간 동작이 가능하였고 부동소수점 연산 결과와 고정소수점 연산 결과를 비교하여 60 dB 이상의 높은 SNR을 가짐을 확인하였다. 또한 사운드 입출력과 호스트 통신을 통하여 EVM 보드에서 실시간으로 동작함을 확인하였다.

In this paper, we present the implementation of filterbank for MPEG-2 Advanced Audio Coding (AAC) decoder with VHDL. The filterbank of AAC employs a technique called time-domain aliasing cancellation (TDAC). In order to make the algorithm more efficiently, we decompose and reorganize the filterbank algorithm lot the high speed decoding process and lower computational cost. And we make this filterbank algorithm to be used with other modules of AAC decoder in parallel processing.

In this paper, we present a new adaptive filter structure which is based on polyphase decomposition of the filter to be adapted. This structure uses wavelet transform to acquire transform-domain coefficients of the input signal. With this coefficients RLS algorithm is used for adaptation. Particularly, using the polyphase parallel structure, we can trace the system which has very long impulse response with only increasing the subband, and show that computational savings can be achieved. The proposed structure was applied to system identification for performance estimation and compared with fullband adaptive filter.

In this paper, the relation between the vibration and the sound radiated due to the piezoelectric ESWL (Extra-corporeal Shock Wave Lithotripter) is examined And the relation between the focus and the vibration of the objects is examined. The same experiments with the objects that can be breton are done and the relation between the vibration and the break efficiency of the phantom is experimentally investigated. These results show that the relativity between the power of the peak frequency and the break efficiency can be confirmed.

In this paper, we investigate the distribution of classification accuracies of multiclass problems in the feature space and analyze performances of the conventional feature extraction algorithms. In order to find the distribution of classification accuracies, we sample the feature space and compute the classification accuracy corresponding to each sampling point. Experimental results showed that there exist much better feature sets that the conventional feature extraction algorithms fail to find. In addition, the distribution of classification accuracies is useful for developing and evaluating the feature extraction algorithm.

Wavelet transform used for content-based image retrieval has good performance in texture image. Image features for content-based image retrieval are color, texture, and shape. In this paper, we use color feature extracted from HSI color space known as most similar vision system to human vision system and texture feature extracted from wavelet histogram which has multiresolution property. Proposed method is compared with HSI color histogram method and wavelet histogram method. It is shown better performance.

We propose a method for analyzing the document structure. This method consists of two processes, segmentation and classification. The segmentation first divides a low resolution image, and then finely splits the original document image using projection profiles. The classification deterimines each segmented region as text, line, table or image. An experiment with 238 documents images shows that the segmentation accuracy is 99.1% and the classification accuracy is 97.3%.

In this paper we propose an algorithm that detects, tracks a moving object, and classify whether it is human from the video clip captured under the fixed video camera. It detects the outline of the moving object by finding out the local maximum points of the modulus image, which is the magnitude of the motion vectors. It also estimates the size and the center of the moving object. When the object is detected, the algorithm discriminates whether it is human by segmenting the face. It is segmented by searching the elliptic shape using Hough transform and grouping the skin color region within the elliptic shape.

Almost vision application systems use 2-D information by taking only one camera. Recently it arises to utilize 3-D information, which is distance from camera to object, because 2-D information is not sufficient. Therefore, we take stereo camera system. In motion detection algorithm using stereo vision, it operates like one camera system, which takes advantage of correlation, edge, and difference algorithm, when it detects any motion. At that time, to detect motion, it compares two images, which is from two cameras, to calculate disparity that contains distance information. By disparity, it can compute real distance and size of object information. We describe a motion detection algorithm which computes 3-D distance and object size in real time.

In the closed range space, the parallel two CCD cameras are used to acquire a pair of stereo image. The acquired stereo image are computed with Wavelet Transform repeatedly and including the low frequency component, the image size of those are reduced. It is the pyramid structure. The optimum matching point is searched to the pixel. Then appling the optimum matching point to DLT, it extract the three - dimensional surface coordinate from a stereo image. The direct linear transformation(DLT) method is used to calibrate the stereo camera compute the coordinate on a three dimensional space. To find the parameters for the DLT method, 30 control points which marked on the cylinder type object are used. To improve the matching algorithm, the paper select the pyramid structure for Wavelet Transform. The acquired disparity information is used to represent the really three-dimensional surface coordinate.

Many researches have been performed for human recognition and coding schemes recently. For this situation, we propose an automatic facial feature extraction algorithm. There are two main steps: the face region evaluation from original background image such as office, and the facial feature extraction from the evaluated face region. In the face evaluation, Genetic Algorithm is adopted to search face region in background easily such as office and household in the first step, and Template Matching Method is used to extract the facial feature in the second step. We can extract facial feature more fast and exact by using over the proposed Algorithm.

In this paper, we propose a new algorithm to detect human faces for controling a camera used in video conference. We model the distribution of skin color and set up the standard skin color in YIQ color space. An input video frame image is segmented into skin and non-skin segments by comparing the standard skin color and each pixels in the input video frame. Then, shape filler is applied to select face segments from skin segments. Our algorithm detects human faces in real time to control a camera to capture a human face with a proper size and position.

Human frequently communicate non-linguistic information with gesture. So, we must develop efficient and fast gesture recognition algorithms for more natural human-computer interaction. However, it is difficult to recognize gesture automatically because human's body is three dimensional object with very complex structure. In this paper, we suggest a method which is able to detect key frames and frame changes, and to classify image sequence into some gesture groups. Gesture is classifiable according to moving part of body. First, we detect some frames that motion areas are changed abruptly and save those frames as key frames, and then use the frames to classify sequences. We symbolize each image of classified sequence using Principal Component Analysis(PCA) and clustering algorithm since it is better to use fewer components for representation of gestures. Symbols are used as the input symbols for the Hidden Markov Model(HMM) and recognized as a gesture with probability calculation.

A 2D comic model, a comic-style line drawing model having only eyebrows, eyes, nose and mouth, is much easier to generate facial expressions with small number of points than that of 3D model. In this paper we propose a 3D emotional editor using a 2D comic model, where emotional expressions are represented by using action units(AU) of FACS. Experiments show a possibility that the proposed method could be used efficiently for intelligent sign-language communications between avatars of different languages in the Internet cyberspace.

In this paper, we proposed a wavelet-based digital watermarking algorithm using human visual system and subband-adaptive threshold. After the original image is transformed using discrete wavelet transform(DWT), the perceptually significant coefficients of the each subband excluding the lowest level subbands are utilized to embed the watermark. To select perceptually significant coefficients, we use subband-adaptive threshold. For the selected coefficients, the watermark is embedded by rising HVS. We tested the performance of the proposed algorithm compared with conventional watermarking algorithm by computer simulation. The experimental results show that the proposed algorithm is superior to the conventional algorithm.

A number of theoretical researches have been done in recent years on the restoration of images and a variety of algorithms have been developed to implement noise reduction methods. However the blurring effect has not been perfectly overcome in the process of noise reduction. In this paper, we propose a new approach to image restoration that the blurring effect is significantly decreased and the performance of the noise reduction improves by eliminating the noise in the wavelet transform domain in comparison with the conventional noise reduction methods. The proposed algorithm performs much better than the conventional in the subjective image quality and PSNR performance. It is verified through computer simulations,

A fingerprint core-point detection algorithm is presented in this paper. Core-point is useful for fingerprint classification and also for the fingerprint verification since it giver a reference to a fingerprint. Traditional methods of finding the core-point is introduced. These methods are the method using poincare index and the method using sine component of ridge directions. The proposed method is modified algorithm of the latter using the poincare index. The experimental results show that the proposed algorithm achieves almost the same accuracy with faster speed.

In this paper, we present a color interpolation technique based on artificial neural networks for a single-chip CCD (charge-coupled device) camera with a Bayer color filter array (CFA). Single-chip digital cameras use a color filter array and an interpolation method in order to regenerate high quality color images from sparsely sampled images. We applied 3-layer feedforward neural networks in order to interpolate missing pixel from surrounding pixels. And we compared the proposed method with conventional interpolation methods such as the proposed interpolation algorithm based on neural networks provides a better performance than the conventional interpolation algorithms.