Using video synthesis to depict flowing water is useful in virtual reality, computer games, digital movies and scientific computing. This paper presents a novel algorithm for synthesizing dynamic water scenes through a sample video based on a dynamic texture model. In the paper, we treat the video sample as a 2-D texture image. In order to obtain textons, we analyze the video sample automatically based on dynamic texture model. Then, we utilize a linear dynamic system (LDS) to describe the characteristics of each texton. Using these textons, we synthesize a new video for dynamic flowing water which is prolonged and non-fuzzy in vision. Compared with other classical methods, our method was tested to demonstrate the effectiveness and efficiency with several video samples.

In this paper, a novel neighborhood metric of histogram equalization (HE) algorithm for contrast enhancement is presented. We present a refinement of HE using neighborhood metrics with a general framework which orders pixels based on a sequence of sorting functions which uses both global and local information to remap the image greylevels. We tested a novel sorting key with the suggestion of using the original image greylevel as the primary key and a novel neighborhood distinction metric as the secondary key, and compared HE using proposed distinction metric and other HE methods such as global histogram equalization (GHE), HE using voting metric and HE using contrast difference metric. We found that our method can preserve advantages of other metrics, while reducing drawbacks of them and avoiding undesirable over-enhancement that can occur with local histogram equalization (LHE) and other methods.

A 3D stereoscopic image is generated by interdigitating every scene with video editing tools that are rendered by two cameras' views in 3D modeling tools, like Autodesk MAX(R) and Autodesk MAYA(R). However, the depth of object from a static scene and the continuous stereo effect in the view of transformation, are not represented in a natural method. This is because after choosing the settings of arbitrary angle of convergence and the distance between the modeling and those two cameras, the user needs to render the view from both cameras. So, the user needs a process of controlling the camera's interval and rendering repetitively, which takes too much time. Therefore, in this paper, we will propose the 3D stereoscopic image editing system for solving such problems as well as exposing the system's inherent limitations. We can generate the view of two cameras and can confirm the stereo effect in real-time on 3D modeling tools. Then, we can intuitively determine immersion of 3D stereoscopic image in real-time, by using the 3D stereoscopic image preview function.

Silhouette is useful in computer graphics for a number of techniques such as non-photorealistic rendering, silhouette clipping, and blueprint generating. Methods for generating silhouette are classified into three categories: image-based, object-based, and hybrid-based. Hybrid-based method is effective in terms of time complexity but spatial coherence problem still remains. In this paper, we proposed a new hybrid-based method which produces 3D data for silhouette and also guarantees no spatial coherence problem. To verify the efficiency of the proposed algorithm, several experiments are conducted for various 3D models from simple to quite complex. Results show that our algorithm generates no gap between any two consecutive silhouette lines when the silhouette model is magnified significantly.

Image identification is the process of checking whether the query image is the transformed version of the specific original image or not. In this paper, image identification method based on feature composition is proposed. Used features include color distance, texture information and average pixel intensity. We extract color characteristics using color distance and texture information by Modified Generalized Symmetry Transform as well as average intensity of each pixel as features. Individual feature is quantized adaptively to be used as bins of histogram. The histogram is normalized according to data type and it is used as the signature in comparing the query image with database images. In matching part, Manhattan distance is used for measuring distance between two signatures. To evaluate the performance of the proposed method, independent test and accuracy test are achieved. In independent test, 60,433 images are used to evaluate the ability of discrimination between different images. And 4,002 original images and its 29 transformed versions are used in accuracy test, which evaluate the ability that the proposed algorithm can find the original image correctly when some transforms was applied in original image. Experiment results show that the proposed identification method has good performance in accuracy test. And the proposed method is very useful in real environment because of its high accuracy and fast matching capacity.

Human face avatar is important information in nowadays, such as describing real people in virtual world. In this paper, we have presented a face avatar creation and warping algorithm by using face feature analysis method, in order to detect face feature, we utilized local mean method based on facial feature appearance and face geometric information. Then detect facial candidates by using it's character in $YC_bC_r$ color space. Meanwhile, we also defined the rules which are based on face geometric information to limit searching range. For analyzing face feature, we used face feature points to describe their feature, and analyzed geometry relationship of these feature points to create the face avatar. Then we have carried out simulation on PC and embed mobile device such as PDA and mobile phone to evaluate efficiency of the proposed algorithm. From the simulation results, we can confirm that our proposed algorithm will have an outstanding performance and it's execution speed can also be acceptable.

Human recognition on camera is an interesting topic in computer vision. While fingerprint and face recognition have been become common, gait is considered as a new biometric feature for distance recognition. In this paper, we propose a gait recognition algorithm based on the knee angle, 2 feet distance, walking velocity and head direction of a person who appear in camera view on one gait cycle. The background subtraction method firstly use for binary moving object extraction and then base on it we continue detect the leg region, head region and get gait features (leg angle, leg swing amplitude). Another feature, walking speed, also can be detected after a gait cycle finished. And then, we compute the errors between calculated features and stored features for recognition. This method gives good results when we performed testing using indoor and outdoor landscape in both lateral, oblique view.

This paper presents a blind video watermarking algorithm that has the robustness against spatial, temporal, and SNR scalability and transcoding for the copyright protection of video contents in heterogeneous multimedia service. The proposed process of watermark embedding and detecting is accomplished on base layer for considering spatial scalability. The watermark consists of the string and the ordering number of string for considering temporal scalability. Thus, each of frames has the bitstream of one character and a ordering number of its character. To robust against FGS, the proposed algorithm quantizes low and middle frequency coefficients in ROI region of each of frames and embeds its watermark bitstream into the specific bits of the quantized coefficients. Experimental results verified that the proposed algorithm satisfies the invisibility of watermark and also has the robustness against spatial scalability, temporal scalability and FGS.

A simple efficient method of spotting and recognizing hand gestures in video is presented using a network of hidden Markov models and dynamic programming search algorithm. The description starts from designing a set of isolated trajectory models which are stochastic and robust enough to characterize highly variable patterns like human motion, handwriting, and speech. Those models are interconnected to form a single big network termed a spotting network or a spotter that models a continuous stream of gestures and non-gestures as well. The inference over the model is based on dynamic programming. The proposed model is highly efficient and can readily be extended to a variety of recurrent pattern recognition tasks. The test result without any engineering has shown the potential for practical application. At the end of the paper we add some related experimental result that has been obtained using a different model - dynamic Bayesian network - which is also a type of stochastic model.

In this paper, two-stage pipelined floating-point arithmetic unit (FP-AU) is designed. The FP-AU processor supports seventeen operations to apply 3D graphics processor and has area-efficient and low-latency architecture that makes use of modified dual-path computation scheme, new normalization circuit, and modified compound adder based on flagged prefix adder. The FP-AU has about 4-ns delay time at logic synthesis condition using $0.18{\mu}m$ CMOS standard cell library and consists of about 5,930 gates. Because it has 250 MFLOPS execution rate and supports saturated arithmetic including a number of graphics-oriented operations, it is applicable to mobile 3D graphics accelerator efficiently.

This paper presents high-spread (HS) random interleavers based interleave-division multiple access (IDMA) scheme for the 4th generation mobile radio system. High-spread feature of a random interleaver offers high-spread characteristics to interleavers and thus produces extrinsic values with low correlation. As interleavers are key components for user separation in the IDMA, the HS interleavers with this feature are employed and analyzed in the IDMA for performance improvement. In addition, by replacing random interleavers with the HS interleavers in the IDMA, bandwidth efficiency is achieved by means of reducing the length of the repetition code. Performance evaluation shows that the proposed scheme of the IDMA with the HS interleavers provides superior BER performance and improved bandwidth efficiency.

ZigBee devices are limited in resources especially on power and computational capacity but also require real-time operation at MAC layer. Therefore, it is important to take those requirement into consideration of system software design. In this paper, we proposed a compact system software design to support simultaneously ZigBee and IEEE802.15.4. The design strictly respects the resource and real-time constraints while being optimized for specific functions of both Zigbee and IEEE802.15.4. Various evaluations are done to show significant metrics of our design.

The ID/password method is the most classical method among authentication techniques on the internet, and is performed more easily and successfully than other methods. However, it is a vulnerable method against attacks such as eavesdropping or replay attack. To overcome this problem, OTP technique is used. The most popular OTP is HOTP algorithm, which is based on one-way hash function SHA-1. As recent researches show the weakness of the hash function, we need a new algorithm to replace HOTP. In this paper we propose a new OTP algorithm using the MAC(Message Authentication Code) based on AES. We also show that the new OTP outperforms HOTP experimentally.

In this paper, we propose a dynamic keyed block encryption algorithm. Most existing encryption algorithms are designed such that the key is not changed. Therefore, they have a disadvantage that plaintext could be easily exposed by differential and linear cryptanalysis. In the proposed algorithm, several key generators are designed, and a key generator is attached to the encryption procedure. After performing the encryption procedure, ciphertext and the initial key generating values are transferred to the receiver's key generator for decryption. Through simulation, the proposed algorithm is verified to satisfy the requirements of real-time processing and proved to have a high strength. It can be applied to practical use.

Human detection techniques in outdoor scenes have been studied for a long time to watch suspicious movements or to keep someone from danger. However there are few methods of human detection in overhead or near-field view scenes, while lots of human detection methods in far-field view scenes have been developed. In this paper, a set of five features useful for human detection in overhead view scenes and another set of four useful features in near-field view scenes are suggested. Eight feature-candidates are first extracted by analyzing geometrically varying characteristics of moving objects in samples of video sequences. Then highly contributed features for each view scene to classifying human from other moving objects are selected among them by using a neural network learning technique. Through experiments with hundreds of moving objects, we found that each set of features is very useful for human detection and classification accuracy for overhead view and near-field view scenes was over 90%. The suggested sets of features can be used effectively in a PTZ camera based surveillance system where both the overhead and near-field view scenes appear.

The work of creating character motion needs the higher professional technology and sense and the creating work of realistic and natural motion possess the most part of production term. In this paper we introduce the easy and convenient 3D animation authoring tool which makes the motion based on whole-body inverse kinematics and motion editing function. The proposed 3D animation authoring tool uses the forward kinematics using quaternion and whole-body inverse kinematics to determine the rotation and displacement of skeleton. Also, it provides the motion editing function using multi-level B-spline with quasi-interpolant. By using the proposed tool, we can make 3D animation easily and conveniently.

This research proposes an alternative approach to machine learning based ones for text categorization. For using machine learning based approaches for any task of text mining, documents should be encoded into numerical vectors; it causes two problems: huge dimensionality and sparse distribution. Although there are various tasks of text mining such as text categorization, text clustering, and text summarization, the scope of this research is restricted to text categorization. The idea of this research is to avoid the two problems by encoding a document or documents into a table, instead of numerical vectors. Therefore, the goal of this research is to improve the performance of text categorization by proposing approaches, which are free from the two problems.

It becomes enabled to provide variety of multimedia contents through mobile service with the development of high-speed 3rd generation mobile communication and handsets. MMS (Multimedia Messaging Service) can be displayed in the presentation format which is unified the various multimedia contents such as text, audio, image, video, etc. It is applicable as a new type of ubiquitous learning. In this study we propose to design a mobile learning system by providing profiles which meets the standard of CC/PP and by generating multimedia messages based on SMIL language through the adaptation steps according to the learning environment, the content type, and the device property of learners.

The software once developed enters in to the $2^{nd}$ phase of its useful operational life, where it performs its functions for which it has been developed. This is an important phase of software life, wherein the developers and users have to assess the performance of the software to prolong its operational life with efficiency, effectiveness and economy. Performance of the software is based on the measurement of the quality characteristics to ascertain that it is meeting or exceeding the needs of customers in terms of its functionality, usability, efficiency, reliability, availability, maintainability, portability etc. These software quality attributes defined under ISO 9126 provide an overall good framework for assessing the performance of the software. This paper describes a Software Performance Assessment (SPA) model using the Goal-Question-Metric (GQM) paradigm which has been applied to the operational software in real context with successful results.