Spatio-Temporal Video Motion Detection Using Marked-Watershed and Morphological Operations

In this article, we describe a moving object detection method developed based on spatio-temporal information and marked-watershed for extracting the moving objects from a video sequence. The algorithm begins with difference image between two adjacent frames and, using the Canny operator on the difference image, determines the initial edge mask for the object in motion Morphological operators are applied to the initial edge map to obtain a temporal segmentation mask of the moving object and binary marker image of the foreground and background, which is subject to the watershed thresholding. The markers are used to modify multi-scale morphological gradient image of the current frame. Finally, the watershed algorithm is performed on the modified gradients to locate the non-stationary objects accurately in the spatial domain of motion frames. Experimental results show that the proposed technique can overcome the shortcoming of over-segmentation of the watershed algorithm. In computationally efficient way, it segments and extracts semantically meaningful objects, which are in slow or fast motion from the video frames of scenes involving complex background. Performance evaluation yields that the detection accuracy can be as high as 98% to 99% for different video sequences.     

基于颜色和特征匹配的视频图像人脸检测实现技术

A face detection method using statistical skin-color model and facial feature matching is presented in this paper.According to skin-color distribution in YUV color space,we develope a statistical skin-color model through interactive sample training and learning.Using this method we convert the color image to binary image and then segment face-candidate regions in the video images.In order to improve the quality of binary image and remove unwanted noises,filtering and mathematical morphology are empolied.After these two processing,we use facial feature matching for further detection.The presence or absence of a face in each region is verified by means of mouth detector based on a template matching method.The experimental results show the proposed method has the features of high speed and high efficiency,but also robust to face variation to some extent.So it is suitable to be applied to real-time face detection and tracking in video sequences.     

Robust Video Text Detection with Morphological Filtering Enhanced MSER

Video text detection is a challenging problem, since video image background is generally complex and its subtitles often have the problems of color bleeding, fuzzy boundaries and low contrast due to vi...     

Edge detection algorithm based on ICA-domain shrinkage in noisy images

We propose a robust edge detection method based on ICA-domain shrinkage （in- dependent component analysis）. It is known that most basis functions extracted from natural images by ICA are sparse and similar to localized and oriented receptive fields, and in the proposed edge detection method, a target image is first transformed by ICA basis functions and then the edges are detected or recon- structed with sparse components. Furthermore, by applying a shrinkage algorithm to filter out the components of noise in ICA-domain, we can readily obtain the sparse components of the original image, resulting in a kind of robust edge detec- tion even for a noisy image with a very low SN ratio. The efficiency of the proposed method is demonstrated by experiments with some natural images.     

Halftoning based algorithms for image hiding

Digital halftoning is an important process to convert a continuous-tone image into a binary image with pure black and white pixels. This process is necessary when printing a monochrome or color image by a printer with limited number of ink colors. The main contribution of this paper is to present a halftoning method that conceals a binary image into two binary images. More specifically, three distinct gray scale images are given, such that one of them should be hidden in the other two gray scale images. Our halftoning method generates three binary images that reproduce the tone of the corresponding original three gray scale images. Quite surprisingly, the secret binary image can be seen by overlapping the other two binary images. In other words, the secret binary image is hidden in two public binary images. Also, it is very hard to guess the secret images using only one of the two public images, and both of these two public images are necessary to get the secret image. Another contribution of this paper is to extend our halftoning method to hide one image and more than one image into more than two images. The resulting images show that our halftoning method hides and recovers the original images. Hence, our halftoning technique can be used for watermarking as well as amusement purpose.     

Single image haze removal via depth-based contrast stretching transform

Under the weather of haze, fog, or smoke, outdoor images show poor visibility and low contrast.Low contrast results in the difficulty for carrying out basic local feature(e.g., interest points and edges) detection algorithms, which are necessary procedures in some computer vision applications. Hence, increasing contrast of degraded images is very important since it is helpful in finding more distinct features from haze images.However, few single image haze removal methods can simultaneously achieve clear visibility, sufficiently high contrast, and simplicity. In this paper, we propose an intuitive and effective method, called the depth-based contrast stretching transform(DCST), to simultaneously obtain clear visibility and enhance contrast of a single haze gray image. The DCST stretches the contrast of haze images based on the coarse depth layers of scenes.Our method is simple and almost real time and can be extended to color images. We analyze in detail that the image stretched by the DCST has a higher local contrast than the image recovered via the physical-based model.Experiments demonstrate that images stretched by the DCST have excellent visibility and contrast compared with a few existing algorithms. Compelling performance is also presented by comparing the proposed method with other representative methods in the application of local feature detection.     

Document Analysis by Crosscount Approach

In this paper a new feature called crosscount for document analysis is introduced.The reature crosscount is a function of white line segment with its start on the edge of document images.It reflects not only the contour of image,but also the periodicity of white lines(background)and text lines in the document images.In complex printed-page layouts,there are different blocks such as textual,graphical,tabular,and so on.Of these blocks,textual ones have the most obvious periodicity with their homogeneous white lines arranged regularly.The important property of textual blocks can be extracted by crosscount functions.here the document layouts are classified into three classes on the basis of their physical structures.Then the definition and properties of the crosscount function are described.According to the classification of document layouts,the application of this new feature to different types of document images‘ analysis and understanding is discussed.     

Contrast evaluation methods for natural color images in display systems: within- and cross-content evaluations

Contrast evaluation can be used as a criterion to evaluate performance of contrast enhancement algorithms and to compare contrast capability of display systems. This paper deals with contrast evaluation models for natural color images. Two separate models are defined for within- and cross-content evaluations. The former is to differentiate the perceived contrast of the images with the same content. The latter is to discriminate the differences in contrast among the images with different contents. Perception mechanisms are quite different for within- and cross-content evaluations. Local contrast plays an important role in within-content evaluation. In contrast, global contrast dominates the contrast perception for cross-content evaluation. Results of human visual experiments show that the proposed evaluation models outperform previous methods for both within- and cross-content evaluations.     

Affective Image Colorization

Colorization of gray-scale images has attracted many attentions for a long time.An important role of image color is the conveyer of emotions(through color themes).The colorization with an undesired color theme is less useful,even it is semantically correct.However this has been rarely considered.Automatic colorization respecting both the semantics and the emotions is undoubtedly a challenge.In this paper,we propose a complete system for affective image colorization.We only need the user to assist object segmentation along with text labels and an affective word.First,the text labels along with other object characters are jointly used to filter the internet images to give each object a set of semantically correct reference images.Second,we select a set of color themes according to the affective word based on art theories.With these themes,a generic algorithm is used to select the best reference for each object,balancing various requirements.Finally,we propose a hybrid texture synthesis approach for colorization.To the best of our knowledge,it is the first system which is able to efficiently colorize a gray-scale image semantically by an emotionally controllable fashion.Our experiments show the effectiveness of our system,especially the benefit compared with the previous Markov random field(MRF) based method.     

Anti-aliased rendering of water surface

Water surface is one of the most important components of landscape scenes. When rendering spacious water surface such as that of the lakes and reservoirs, aliasing and/or moiré artifacts frequently occur in the regious far from the viewpoint. This is because water surface consists of stochastic water waves which are usually modeled by periodic bump mapping. The incident rays on the water surface are actually scattered by the bumped waves, and the reflected rays at each sample point are distributed in a solid angle. To get rid of the artifacts of moiré pattern, we estimate this solid angle of reflected rays and trace these rays. An image-based accelerating method is adopted so that the contribution of each reflected ray can be quickly obtained without elaborate intersection calculation. We also demonstrate anti-aliased shadows of sunlight and skylight on the water surface. Both the rendered images and animations show excellent effects on the water surface of a reservoir. The first, third and fifth co-authors were partially supported by the National Natural Science Foundation of China (Grant Nos. 60021201 and 60373035), Key Research Project of Ministry of Education (Grant No.01094) and the National Grand Fundamental Research 973 Program of China (Grant No.2002CB312102). Xue-Ying Qin is an associated professor of State Key Laboratory of CAD&CG, Zhejiang University. She received her Ph.D. degree from Hiroshima University in 2001, B.S. and M.S. degrees in Mathematics from Peking University in 1988 and from Zhejiang University in 1991, respectively. Her research interests include computer graphics, visions and image processing. Eihachiro Nakamae is currently Chairman of Sanei Co. He was granted the title of emeritus professor from both Hiroshima University and Hiroshima Institute of Technology. He was appointed as a researcher associate at Hiroshima University in 1956, a professor from 1968 to 1992 and an associated researcher at Clarkson College of Technology, Potsdam, N.Y., from 1973 to 1974. He was a professor at Hiroshima Prefectural University from 1992 to 1995 and a professor at Hiroshima Institute of Technology from a996 to the end of March 1999. He received his B.E., M.E., and Ph.D. degrees in electrical engineering in 1954, 1956, and 1967 from Waseda University. His research interests include computer graphics, image processing and electric machinery. He is a member of IEEE, ACM, CGS, Eurographics, IEE of Japan, and IPS of Japan. Wei Hua received his Ph.D. degree in applied mathematics from Zhejiang University in 2002. He joined the CAD&CG State Key Lab in 2002. His main interests include real-time simulation and rendering, virtual reality and software engineering. Yasuo Nagai is now an associate professor of Hiroshima Institute of Technology. He was appointed a researcher associate at Hiroshima Institute of Technology in 1965, and an associate professor in 1984. His research interests include computer graphics and image processing. He is a member of IEE, IEICE, IPSJ, and ITE of Japan. Qun-Sheng Peng was born in 1947. He received his Ph.D. degree in computer science from the University of East Anglia, U.K., in 1983. He is a professor and his research interests include computer graphics, computer animation, virtual reality, and point-based modeling and rendering.     

Learning Horn definitions: Theory and an application to planning

A Horn definition is a set of Horn clauses with the same predicate in all head literals. In this paper, we consider learning non-recursive, first-order Horn definitions from entailment. We show that this class is exactly learnable from equivalence and membership queries. It follows then that this class is PAC learnable using examples and membership queries. Finally, we apply our results to learning control knowledge for efficient planning in the form of goal-decomposition rules. Chandra Reddy, Ph.D.: He is currently a doctoral student in the Department of Computer Science at Oregon State University. He is completing his Ph.D. on June 30, 1998. His dissertation is entitled “Learning Hierarchical Decomposition Rules for Planning: An Inductive Logic Programming Approach.” Earlier, he had an M. Tech in Artificial Intelligence and Robotics from University of Hyderabad, India, and an M.Sc.(tech) in Computer Science from Birla Institute of Technology and Science, India. His current research interests broadly fall under machine learning and planning/scheduling—more specifically, inductive logic programming, speedup learning, data mining, and hierarchical planning and optimization. Prasad Tadepalli, Ph.D.: He has an M.Tech in Computer Science from Indian Institute of Technology, Madras, India and a Ph.D. from Rutgers University, New Brunswick, USA. He joined Oregon State University, Corvallis, as an assistant professor in 1989. He is now an associate professor in the Department of Computer Science of Oregon State University. His main area of research is machine learning, including reinforcement learning, inductive logic programming, and computational learning theory, with applications to classification, planning, scheduling, manufacturing, and information retrieval.     

Digital Image Watermarking Based on Discrete Wavelet Transform

This paper aims at digital watermark which is a new popular research topic recently,presents some methods to embed digital watermark based on modifying frequency coefficients in discrete wavelet transform(DWT) domian,Fist,the,the present progress of digital watermark is briefly introduced;after that,starting from Pitas‘s method and discarding his pseudo random number method,the authors use a digital image scrambling technology as preprocessing for digital watermarking ,Then the authors discuss how to embed a 1-bit digital image as watermark in frequency domain.Finally another digital watermarking method is given in which3-D DWT is used to transform a given digtial image .Based on the experimental results ,it is shown that the proposed methods are robust to a large extent.     

An integrated edge detection method using mathematical morphology

This paper presents an edge detection method based on mathematical morphology. The proposed scheme consists of four steps: preprocessing, edge extraction, edge decision, and postprocessing. In the preprocessing step, a morphological central transformation is applied to remove noise. In the edge extraction and decision steps, a morphological edge extractor is designed to estimate the edge information of an image, and an edge decision criterion is followed to determine whether a pixel is an edge or not. In the postprocessing step, the morphological hit-or-miss transformation is utilized to improve the correctness of the detected edges. It is proved theoretically for the correctness and effectiveness for detecting ideal edges. Experimental results show that the proposed method works well on both artificial and real images. The text was submitted by the authors in English. Chin-Pan Huang was born in 1959 in Taiwan, Republic of China. He received the B.S. and M.S. degrees in electrical engineering from Chung Cheng Institute of Technology, Taiwan, in 1981 and in 1985, respectively. In 1996, he received the Ph.D. degree in electrical engineering from the University of Pittsburgh in the United States. From 1996 to 2002, he was an associate scientist of the Electronic System Division in Chung Shan Institute of Science and Technology. He then joined the Department of Computer and Communication Engineering at Ming Chuan University in August 2002 and is currently an assistant professor there. His recent research interests include data compression, computer vision, digital image processing, and pattern recognition. Ran-Zan Wang was born in 1972 in Fukien, Republic of China. He received his B.S. degree in computer engineering and science in 1994 and M.S. degree in electrical engineering and computer science in 1996, both from Yuan-Ze University. In 2001, he received his Ph.D. degree in computer and information science from National Chiao Tung University. In 2001–2002, he was an assistant professor at the Department of Computer Engineering at the Van Nung Institute of Technology. He joined the Department of Computer and Communication Engineering at Ming Chuan University in August 2002 and is currently an assistant professor there. His recent research interests include data hiding and digital watermarking, image processing, and pattern recognition. Dr. Wang is a member of the Phi Tau Phi Scholastic Honor Society.     

A new method of embedded fourth order with four stages to study raster CNN simulation

A new Runge-Kutta （PK） fourth order with four stages embedded method with error control is presentea m this paper for raster simulation in cellular neural network （CNN） environment. Through versatile algorithm, single layer/raster CNN array is implemented by incorporating the proposed technique. Simulation results have been obtained, and comparison has also been carried out to show the efficiency of the proposed numerical integration algorithm. The analytic expressions for local truncation error and global truncation error are derived. It is seen that the RK-embedded root mean square outperforms the RK-embedded Heronian mean and RK-embedded harmonic mean.     

Leakage current estimation of CMOS circuit with stack effect

Leakage current of CMOS circuit increases dramatically with the technology scaling down and has become a critical issue of high performance system. Subthreshold, gate and reverse biased junction band-to-band tunneling (BTBT) leakages are considered three main determinants of total leakage current. Up to now, how to accurately estimate leakage current of large-scale circuits within endurable time remains unsolved, even though accurate leakage models have been widely discussed. In this paper, the authors first dip into the stack effect of CMOS technology and propose a new simple gate-level leakage current model. Then, a table-lookup based total leakage current simulator is built up according to the model. To validate the simulator, accurate leakage current is simulated at circuit level using popular simulator HSPICE for comparison. Some further studies such as maximum leakage current estimation, minimum leakage current generation and a high-level average leakage current macromodel are introduced in detail. Experiments on ISCAS85 and ISCAS89 benchmarks demonstrate that the two proposed leakage current estimation methods are very accurate and efficient.     

Step-coordination algorithm of traffic control based on multi-agent system

Aiming at the deficiency of conventional traffic control method, this paper proposes a new method based on multi-agent technology for traffic control. Different from many existing methods, this paper distinguishes traffic control on the basis of the agent technology from conventional traffic control method. The composition and structure of a multi-agent system （MAS） is first discussed. Then, the step-coordination strategies of intersection-agent, segment-agent, and area-agent are put forward. The advantages of the algorithm are demonstrated by a simulation study.     

BCL—3：Aigh Performance Basic Communication Protocol for Commodity Superserver DAWNING—3000

This paper introduces the design and implemetation of BCL-3,a high performance low-level communication software running on a cluster of SMPs(CLUMPS) called DAWNING-3000,BCL-3 provides flexible and sufficient functionality to fulfill the communication requirements of fundamental system software developed for DAWNING-3000 while guaranteeing security,scalability,and reliability,Important features of BCL-3 are presented in the paper,including special support for SMP and heterogeneous network environment,semiuser-level communication,reliable and ordered data transfer and scalable flow control,The performance evaluation of BCL-3 over Myrinet is also given.     

Blending parametric patches with subdivision surfaces

In this paper the problem of blending parametric surfaces using subdivision patches is discussed.A new approach,named removing-boundary,is presented to generate piecewise-smooth subdivision surfaces through discarding the outmost quadrilaterals of the open meshes derived by each subdivision step.Then the approach is employed both to blend parametric bicubic B-spline surfaces and to fill n-sided holes.It is easy to produce piecewise-smooth subdivision surfaces with both convex and concave corners on the boundary,and limit surfaces are guaranteed to be C^2 continuous on the boundaries except for a few singular points by the removing-boundary approach Thus the blending method is very efficient and the blending surface generated is of good effect.     

BIST design for detecting multiple stuck-open faults in CMOS circuits using transition count

This paper presents a built-in self-test(BIST) scheme for detecting all robustly testable multiple stuck-open faults confined to any single complex cell of a CMOS circuit.The test pattern generator(TPG) generates all n.2^n single-input-change(SIC) orderd test pairs design is universal,i.e.,independent of the structure and functionality of the CUT.A counter that counts the number of alternate transitions at the output of the CUT,is used as a signature analyzer(SA).The design of TPG and SA is simple and no special design-or synthesis-for-testability techniques and /or additional control lines are needed.