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Mining Top-K Frequent and Flexible pattern from Sequences

Mining Top-K Frequent and Flexible Pattern from Sequences

引用

2011 international conference on Intelligent computing and Integrated Systems(ICISS 2011)

作者： Zhang Junyan Information Science and Technology College Chengdu University University Key Laboratory of pattern recognition and Intelligent information Processing, Sichuan Province Chengdu, China Min Fan School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu, China

pattern Mining is a popular issue in biological sequence analysis. With the introduction of wildcard gaps, more interesting patterns can be mined. In this paper, we propose a new definition related to pattern frequency, under which the Apriori property holds. We define a pattern mining problem called Ming top-JiT Frequent patterns (MFP), where gaps are mined instead of specified. Compared with existing problems, MFP does not require any domain knowledge of the user. However, theoretical analysis and experimental results show that MFP favors inflexible patterns. We then define another problem where the flexibility threshold of each gap is specified by the user. The problem is called Mining top-K Frequent and Flexible patterns (MF2P). We develop algorithm with polynomial complexities for both problems. patterns can grow from both sides. Some interesting biological patterns mined by our algorithms are discussed.

关键词： pattern mining sequence wildcard gap constraints

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Automatic license plate detection based on connected component analysis and template matching

Automatic license plate detection based on connected compone...

引用

international conference on Intelligent Control and Information Processing (ICICIP)

作者： Miao Ligang Yue Yongjuan Department of Electronics Information Northeastern University Qinhuangdao Hebei China College of computing & communication Engineering Chinese Academy and Sciences Beijing China Patent Examination Cooperation Center of SIPO Beijing China

This paper proposes a novel method for license plate(LP) detection from images with complex background. First, it segments images with an adaptive binarization method to avoid the problem that nonuniform illumination creates, and some undesired image areas are removed by limiting the range of region properties of connected components(CCs). Secondly, CC analysis is used to construct nearest neighbor chain(NNC) for detection of candidate LP regions(LP-NNC). The average height and direction of each LP-NNC is estimated to deal with images acquired from different view or distances. Thirdly, two variable-length square templates are designed to match horizontal and vertical projections of LP image gradients. They are combined to verify all candidate LP regions, and the most possible region is selected as the true LP region. Experiment results on various types of LP images show that this proposed method has achieved desired detection result for complex scenes.

关键词： Licenses Lighting Image edge detection Image segmentation pattern recognition Image color analysis Computer science

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MULTIPLE FEATURES-BASED IMAGE RETRIEVAL

MULTIPLE FEATURES-BASED IMAGE RETRIEVAL

引用

2011 4th IEEE international conference on Broadband Network & Multimedia Technology(第四届IEEE宽带网络与多媒体国际会议 4th IEEE IC-BNMT2011)

作者： Yanyan Gao Honggang Zhang Jun Guo Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing 100876 China

Color and texture information are two important visual features of an image. In this paper, an efficient content-based image retrieval system is proposed based on color and texture feature. The color feature is extracted by quantifying the HSV color space into non-equal intervals and the color feature is represented by color histogram. Texture feature is obtained by local binary pattern (LBP). When computing the similarity between query image and target images in the database, Gaussian normalization is exploited on the feature space and distant space. And then the linear combination of normalized distances for color and texture is performed to obtain the similarity as the index of image. The exhaustive search scheme is used for retrieval, and the evaluation criterion is precision and recall about the number of returned images. The results of experiments demonstrate the efficiency of the proposed system.

关键词： content-based image retrieval color feature texture feature multi-feature

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The Final Sense Reverse Engineering Electroencephalography

The Final Sense Reverse Engineering Electroencephalography

引用

The 2011 international conference on computing,Information and Control(ICCIC 2011)

作者： Mohammed Zahid Aslam Alpha College of Engineering Visvesvaraya Technological University

The human brain has the amazing ability to bombard itself with millions of bits of diverse information every day. It must also be able to store and convert these intelligent thoughts. In simpler terms,it does this by evaluating,sorting,figuring and redirecting information based on sequences and *** data being processed by the brain is already being studied by EEG(Electroencephalogram) at various levels of research and for clinical purposes. This paper introduces the idea of reverse engineering the concept used in EEG's and "write" data into the brain. This device will apply the required voltage in micro volts to the different parts of the brain externally using EEG electrodes. Thus instead of the basic senses converting physical images and characters,sounds etc into certain voltages being transmitted to the brain,an external device(such as an EEG) can convey the information to the brain.

关键词： Brain Electroencephalography Medical treatment pattern recognition stochastic automata

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VIDEO OBJECT TRACKING WITH DIFFERENTIAL STRUCTURAL SIMILARITY INDEX

VIDEO OBJECT TRACKING WITH DIFFERENTIAL STRUCTURAL SIMILARIT...

引用

IEEE international conference on Acoustics, Speech and Signal Processing

作者： Artur Loza Fanglin Wang Jie Yang Lyudmila Mihaylova Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China School of Computing and Communications Lancaster University UK

ISBN: (纸本)9781457705380

The Structural SIMilarity Measure (SSIM) combined with the sequential Monte Carlo approach has been shown [1] to achieve more reliable video object tracking performance, compared with similar methods based on colour and edge histograms and Bhattacharyya distance. However, the combined use of the structural similarity and a particle filter results in increased computational complexity of the algorithm. In this paper, a novel fast approach for video tracking based on the structural similarity measure is presented. The tracking algorithm proposed determines the state of the target (location, size) based on the gradient ascent procedure applied to the structural similarity surface of the video frame, thus avoiding computationally expensive sampling of the state space. The new method, while being computationally less expensive, has shown higher accuracy compared with the standard mean shift algorithm and the SSIM Particle Filter (SSIM-PF) [1] and its performance is illustrated over real video sequences.

关键词： Tracking structural similarity gradient ascent tracking similar measure Videotapes Video object Particle filters complexity classes state space

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Automatic document image mosaicing algorithm with hand-held camera

Automatic document image mosaicing algorithm with hand-held ...

引用

international conference on Intelligent Control and Information Processing (ICICIP)

This paper presents an image mosaicing method for camera-captured document images, and it can be used to stitch multiple overlapping document images into a large high resolution image. First, we use the nearest-neighbor(NN) clustering technique in document skew rectification to locate the horizontal vanishing point of the text plane. Secondly we partition the image into multiple overlapping blocks centered with the centroid of each connected component(CC), and propose a run-length opening algorithm(RLOA) to compute the local orientation of vertical character stroke(VSB), which is used to locate the document's vertical vanishing point. Thirdly, a three-step hierarchical rectification method is proposed to rectify document images. Finally, it uses local alignment constraints of all the overlapping image pairs to construct global alignment model, thus, to eliminate the error accumulation effectively. This method is unique in not calibrating the internal and external camera parameters in advance and not restricting the camera position, and it can produce a high resolution and accurate full page mosaic from small image patches of a document.

关键词： Estimation pattern recognition Transforms Digital cameras Clustering algorithms Robustness

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MULTIPLE FEATURES-BASED IMAGE RETRIEVAL

MULTIPLE FEATURES-BASED IMAGE RETRIEVAL

引用

2011 4th IEEE international conference on Broadband Network and Multimedia Technology

作者： Yanyan Gao,Honggang Zhang,Jun Guo pattern recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications,Beijing 100876,China

Color and texture information are two important visual features of an *** this paper,an efficient content-based image retrieval system is proposed based on color and texture *** color feature is extracted by quantifying the HSV color space into non-equal intervals and the color feature is represented by color *** feature is obtained by local binary pattern(LBP). When computing the similarity between query image and target images in the database,Gaussian normalization is exploited on the feature space and distant *** then the linear combination of normalized distances for color and texture is performed to obtain the similarity as the index of *** exhaustive search scheme is used for retrieval,and the evaluation criterion is precision and recall about the number of returned images. The results of experiments demonstrate the efficiency of the proposed system.

关键词： content-based image retrieval color feature texture feature multi-feature

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Real-time RGB-D mapping and 3-D modeling on the GPU using the random ball cover data structure

Real-time RGB-D mapping and 3-D modeling on the GPU using th...

引用

international conference on Computer Vision Workshops (ICCV Workshops)

作者： Dominik Neumann Felix Lugauer Sebastian Bauer Jakob Wasza Joachim Hornegger Pattern Recognition Lab Department of Computer Science Friedrich-Alexander-Universität Erlangen-Nürnberg Germany

The modeling of three-dimensional scene geometry from temporal point cloud streams is of particular interest for a variety of computer vision applications. With the advent of RGB-D imaging devices that deliver dense, metric and textured 6-D data in real-time, on-the-fly reconstruction of static environments has come into reach. In this paper, we propose a system for real-time point cloud mapping based on an efficient implementation of the iterative closest point (ICP) algorithm on the graphics processing unit (GPU). In order to achieve robust mappings at real-time performance, our nearest neighbor search evaluates both geometric and photometric information in a direct manner. For acceleration of the search space traversal, we exploit the inherent computing parallelism of GPUs. In this work, we have investigated the fitness of the random ball cover (RBC) data structure and search algorithm, originally proposed for high-dimensional problems, for 6-D data. In particular, we introduce a scheme that enables both fast RBC construction and queries. The proposed system is validated on an indoor scene modeling scenario. For dense data from the Microsoft Kinect sensor (640 × 480 px), our implementation achieved ICP runtimes of

关键词： Iterative closest point algorithm Graphics processing unit Runtime Nearest neighbor searches Real time systems Data structures Solid modeling

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Clustering of Data and Nearest Neighbors Search for pattern recognition with Dimensionality Reduction Using Random Projections

引用

10th international conference on Artificial Intelligence and soft computing (ICAISC 2010)

作者： Skubalska-Rafajlowicz, Ewa Wroclaw Univ Technol Inst Comp Engn Control & Robot PL-50370 Wroclaw Poland

ISBN: (纸本)9783642132070

The dimensionality and the amount of data that need to be processed when intensive data streams are classified may occur prohibitively large. The aim of this paper is to analyze Johnson-Linden-strauss type random projections as an approach to dimensionality reduction in pattern classification based on K-nearest neighbors search. We show that in-class data clustering allows us to retain accuracy recognition rates obtained in the original high-dimensional space also after transformation to a lower dimension.

关键词： pattern recognition

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pattern recognition with Linearly Structured Labels Using Recursive Kernel Estimator

引用

10th international conference on Artificial Intelligence and soft computing (ICAISC 2010)

作者： Krzyzak, Adam Rafajlowicz, Ewaryst Concordia Univ Dept Comp Sci & Software Engn Montreal PQ Canada Wroclaw Univ Technol Inst Comp Engn Control Robotics Wroclaw Poland

ISBN: (纸本)9783642132070

We consider pattern recognition problem when classes and their labels are linearly structured (or ordered). We propose the loss function based on the squared differences between the true and the predicted class labels. The optimal Bayes classifier is derived and then estimated by the recursive kernel estimator. Its consistency is established theoretically. Its RBF-like realization of the classifier is also proposed together with a recursive learning algorithm, which is well suited for on-line applications. The proposed approach was tested in real life example involving classification of moving vehicles.

关键词： pattern recognition

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