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The world of mushrooms - A transdisdplinary approach to human-computer interaction with ambient intelligence

NTT Technical Review 2006年第12期4卷 17-24页

作者： Maeda, Eisaku Minami, Yasuhiro Miyoshi, Masato Sawaki, Minako Sawada, Hiroshi Nakamura, Atsushi Yamato, Junji Yamada, Takeshi Higashinaka, Ryuichiro NTT Communication Science Laboratories Atsugi-shi 243-0198 Japan Ambient Intelligence Research Group Media Intormation Laboratory NTT Communication Science Laboratories IEEE IEICE IPSJ Signal Processing Research Group Media Information Laboratory NTT Communication Science Laboratories ASJ Audio Engineering Society Recognition Research Group Media Information Laboratory NTT Communication Science Laboratories Institute of Image Information and Television Engineers Robotics Society of Japan Emergent Learning and Systems Research Group Innovative Communication Laboratory NTT Communication Science Laboratories ACM Scheduling Society of Japan Knowledge Processing Research Group Innovative Communication Laboratory NTT Communication Science Laboratories Association for Computational Linguistics

This paper provides an update to the January 2006 letter on "ambient intelligence", describing this year's achievements and the latest demonstration systems. The Ambient intelligence Project (also known by the code name project Mushroom) aims to bridge the boundaries between technological fields and thus cover the entire field of communication science.

关键词： Human computer interaction

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Fast DCT-I, DCT-III, and DCT-IV via Moments

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Eurasip Journal on Applied Signal processing 2005年第12期2005卷 1902-1909页

作者： Liu, J.G. Liu, Y.Z. Wang, G.Y. Key Laboratory of Education Huazhong University of Science and Technology Ministry for Image Processing and Intelligence Control Wuhan 430074 China Department of Computer Science and Engineering China University of Geosciences Wuhan 430074 China Key Laboratory of State Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology China Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China

This paper presents a novel approach to compute DCT-I, DCT-III, and DCT-IV. By using a modular mapping and truncating, DCTs are approximated by linear sums of discrete moments computed fast only through additions. This enables us to use computational techniques developed for computing moments to compute DCTs efficiently. We demonstrate this by applying our earlier systolic solution to this problem. The method can also be applied to multidimensional DCTs as well as their inverses. © 2005 Hindawi Publishing Corporation.

关键词： Method of moments

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An algorithm for radar scene matching based on multi-area selection using fuzzy sets

An algorithm for radar scene matching based on multi-area se...

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MIPPR 2005: image Analysis Techniques

作者： Yang, Weidong Zuo, Zhengrong Zhang, Tianxu Mao, Haicen State Key Laboratory of Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

Radar scene matching technique has been widely found in many application fields such as remote sensing, navigation, terrain-map match, scenery variance analysis and so on. Radar image geometry is quite different from that of optical satellite imagery, whose imaging is a slanting imaging of electromagnetic microwave reflection. The different characters between radar image and optical satellite images are very distinct, such as the layover distortion of ground-truth and speckle noise, which degrades the image to such an extent that the features are very unclear and difficult to be extracted. So the factors such as the hypsography, ground truth, sensor altitude and imaging time should be taken into account for radar image and optical image matching. In this paper, we develop an image match algorithm based on reference map multi-area selection using fuzzy sets. image matching is generally a procedure that calculates the similarity measurement between sensed image and the corresponding intercepted image in reference map and it searches the maximum position in the correlation map. Our method adopts a converse matching strategy which selects multi-areas in optical reference map using fuzzy sets as model images, then match them on the sensed image respectively by normalized cross correlation matching algorithm and fuse the match results to get the optimum registered position. Multi-areas selection mainly considers two influence factors such as ground-truth texture features and the hypsography (DEM) of imaging region, which will suppress the influence of great variance imaging region. Experiment results show the method is effective in registering performance and reducing the calculation.

关键词： Remote sensing

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Three-dimensional double directional filter for tracking and detecting moving dim weak target

Three-dimensional double directional filter for tracking and...

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MIPPR 2005: image Analysis Techniques

作者： Li, Meng Zhang, Tianxu Yang, Weidong Mao, Haiceng State Education Commission Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

The aim of the present work is to assess the performance of three-dimensional Double Directional Filtering (TDDDF) algorithm for detecting and tracking a weak moving dim target against a complex cluttered background in infrared image sequences. This paper proposes an novel TDDDF to improve the integrated signal-to-clutter ratio (ISCR) and enhance the three-dimensional directional filter's (TDDF) target energy accumulation ability further. Since the TDDDF do well to whitening noise (or quasi whitening noise) but not so sensitive to complex cloudscene background, prior to the filtering, a newly pre-whitening method termed Spatial-Temporal Adaptive Filtering algorithm is used here to suppress clutter background. Extensive experiment results demonstrate the proposed algorithm's ability in detecting weak dim point target against cloud-cluttered background. Finally, performance comparisons of the proposed algorithm and TDDF, on real IR image data, are presented in which the advantages of the proposed TDDDF filters are shown.

关键词： Tracking (position)

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Runway detection of an unmanned landing aerial vehicle based on vision

Runway detection of an unmanned landing aerial vehicle based...

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MIPPR 2005: SAR and Multispectral image processing

作者： Wang, Hongqun Peng, Jiaxiong Li, Lingling Institute for Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074

When an monocular vision-based unmanned aerial vehicle (UAV) based on vision is flown to the final approach fix to intercept the glide slope without the navigation of Global Positioning System (GPS), the position and orientation of the airport runway in image must be detected accurately so as to a host of suitable procedures have to be followed. The optimum length of the final approach is about five miles from the runway threshold. The front view of the runway, which is achieved at the moment, is very illegible. The approaching marking (cross bar) of the runway are showed as some white spots of high intensity and the complicated backgrounds of the airport are included in the images. In this case, spots with high intensity should be extracted and classified, some of these spots are just the images of the background noises and the pseudo-targets, which can't be separated with the spots of the runway as in the view there is no significant characteristic difference among them ostensibly. Fortunately, in the terrestrial coordinate space, most of the runway marks are located at the apexes of a rectangle, having some geometric relationships. The relationship among the projection coordinates of the runway spots in the images can be determined according to the perspective principle, the constraint condition of the rectangle as well as the front shot constraint condition of the target, by using this relationship, the runway approaching marks can be separated, the position and the direction of the runway in the images can be identified. In this paper, the clustering management is adopted so as to greatly reduce the computing time. The consequence of the experiments shows that by this algorithm, even from a place far away from the runway whose marks are unclear, we also can effectively detect the runway.

关键词： Unmanned vehicles

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基于目标区域特性的海面小目标检测快速算法

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自动化学报 2005年第3期31卷 427-433页

作者：邹玉兰汪国有张磊 Institute for Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan 430074

A fast object detection method based on object region dissimilarity and 1-D AGADM(one dimensional average gray absolute difference maximum) between object and background isproposed for real-time defection of small offshore targets. Then computational complexity, antinoiseperformance, the signal-to-noise ratio (SNR) gain between original images and their results as afunction of SNR of original images and receiver operating characteristic (ROC) curve are analyzed andcompared with those existing methods of small target detection such as two dimensional average grayabsolute difference maximum (2-D AGADM), median contrast filter algorithm and multi-level filteralgorithm. Experimental results and theoretical analysis have shown that the proposed method hasfaster speed and more adaptability to small object shape and also yields improved SNR performance.

关键词：小目标检测快速算法区域特性海面

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A new method for ship classification and recognition

A new method for ship classification and recognition

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MIPPR 2005: image Analysis Techniques

作者： Zhao, Guangzhou Wang, Fei Zhang, Tianxu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China State Key Laboratory for Image Processing and Intelligent Control Wuhan 430074 China

This paper proposes a fast and robust algorithm for classification and recognition of ships based on the Principal Component Analysis (PCA) method. The three-dimensional ship models are achieved by modeling software of MultiGen, and then they are projected by Vega simulating software for two-dimensional ship silhouettes. The PCA method as against the Back-Propagation (BP) neural network method for simulated ship recognition using training and testing experiments, we can see that there is a sharp contrast between them. Some recognition results from simulated data are presented, the correct recognition rate of PCA method improved rapidly for each of the five ship types than that of neural network method, the number of times a ship type is recognized as one of the other ships is reduced greatly.

关键词： Classification (of information)

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Efficient word-level sequential coding scheme of bit plane coding for EBCOT in JPEG2000

Efficient word-level sequential coding scheme of bit plane c...

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9th International Symposium on Consumer Electronics 2005, ISCE 2005

作者： Xiong, Cheng-Yi Tian, Jin-Wen Liu, Jian Institute of Pattern Recognition and Artificial Intelligence South-Center University for Nationalities Huazhong University of Science and Technology Wuhan China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China HUST

The embedded block coding with optimized truncation (EBCOT) is the state-of-the-art coding technique for image compression, which is the heart of the latest still image compression standard JPEG2000. EBCOT can be partitioned into three steps: bit plane coding (BPC), context adaptive binary arithmetic coding (CABAC) and postcompression rate-distortion (PCRD) optimization. The bit plane coding in JPEG2000 is a fractional bit-plane coding method, in which the transformed coefficients of a code block are coded bit plane by bit plane with 3 passes in each bit-plane, and context-decision (CX-D) pair of the coded symbol is generated for CABAC. In this paper, a new word-level sequential (WLS) coding scheme for BPC is presented, which makes all the passes coding be completed in one scan, with the context formation in all bit-planes being performed in parallel and all the samples being coded in sequential. The status variables used in context formation are produced on-the-fly. This new algorithm can efficiently implement both the regular mode and vertical causal one recommended by JPEG2000. The proposed algorithm reduces efficiently the size of memory and the amount of memory accessing, and increases significantly the speed of coding. It is well suited for both software and hardware implementation.1 © IEEE.

关键词： image coding

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A Smart Mathematic Morphology Method for recognition and Understanding of Airfield

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Wuhan University Journal of Natural Sciences 2005年第5期10卷 867-872页

作者： WANG Zhi-cheng TIAN Yan TIAN Jin-wen LIU Jian LIANG Chao-sheng TAO Wen-bin State Education Commission Key Laboratory for Image Processing and Intelligence Control Huazhong University of Science and Technology Wuhan430074 Hubei China Department of Electronics and Information Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Hubei China

A method used for recognition and understanding of airfield based on mathematical morphology is proposed in this paper. The new approach can he divided into three steps. First, to extract the typical geometric structure features of airfield, a segmentation method called recursive Otsu algorithm is employed on an airfield image. Second, thinning and shrinking algorithms are utilized to obtain the contour of airfield with single pixel and to remove diffused small particles. Finally, Radon transform is adopted to extract two typical and important components, primary and secondary runways of airfield exactly. At the same time, region growing algorithm is exploited to get the other components such as parking apron and garages. The experimental results demonstrate that the proposed method gives good performance.

关键词： mathematical morphology shrinking algorithm Radon transform Region growing

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Weighted MLS-SVM for approximation of directional derivatives

Weighted MLS-SVM for approximation of directional derivative...

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MIPPR 2005: image Analysis Techniques

作者： Zheng, Sheng Tian, JinWen Liu, Jian China Three Gorges University Yichang 443002 China Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

Based on statistical learning theory, support vector machine (SVM) is a novel type of learning machine, and it contains polynomial, neural network and radial basis function (RBF) as special cases. The mapped least squares support vector machine (MLS-SVM) is a special least square SVM (LS-SVM), which extends the application of the SVM to the image processing. Based on the MLS-SVM, a family of filters for the approximation of partial derivatives of the digital image surface is designed. Prior information (e.g., local dominant orientation) are incorporated in a two dimension weighted function. The weighted MLS-SVM with the radial basis function kernel is applied to design the proposed filters. Exemplary application of the proposed filters to fingerprint image segmentation is also presented.

关键词： Learning systems

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