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The PAGE (Page Analysis and Ground-Truth Elements) Format Framework

The PAGE (Page Analysis and Ground-Truth Elements) Format Fr...

引用

international conference on pattern recognition

作者： Stefan Pletschacher Apostolos Antonacopoulos Pattern Recognition and Image Analysis Research Laboratory School of Computing Science and Engineering University of Sanford UK

There is a plethora of established and proposed document representation formats but none that can adequately support individual stages within an entire sequence of document image analysis methods (from document image enhancement to layout analysis to OCR) and their evaluation. This paper describes PAGE, a new XML-based page image representation framework that records information on image characteristics (image borders, geometric distortions and corresponding corrections, binarisation etc.) in addition to layout structure and page content. The suitability of the framework to the evaluation of entire workflows as well as individual stages has been extensively validated by using it in high-profile applications such as in public contemporary and historical ground-truthed datasets and in the ICDAR Page Segmentation competition series.

关键词： Layout Text analysis Joining processes Performance evaluation XML Pipelines Optical character recognition software

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The Research of Digital Image Quality Evaluation Method for Beef Tenderness

The Research of Digital Image Quality Evaluation Method for ...

引用

international conference on Computational Intelligence and software Engineering (CiSE)

作者： Jian Wang Guo-min Zhou Agricultural information Institute of CAAS Beijing China

Digital image quality evaluation is a relatively new area of research. In this field, how to choose a good image is an important research content for enhancing the efficiency of pattern recognition system. In this paper, beef images are used as an object of study for computing tenderness. Based on the traditional evaluation method of image quality, the thesis analyzes some factors that affect the quality of digital image and proposes an comprehensive evaluation method combined Spatial Distribution of Edges, Color Distribution , Hue Count, Blur, contrast and brightness. Experiments prove that: Image quality assessment scores marked from the method proposed in this paper are consistent with results gotten from pattern recognition system and the efficiency of pattern recognition system is significantly increased. It means that the proposed approach is effective.

关键词： Image quality pattern recognition Feature extraction Image color analysis Brightness Image recognition Histograms

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SubXPCA versus PCA: A Theoretical Investigation

SubXPCA versus PCA: A Theoretical Investigation

引用

international conference on pattern recognition

作者： Atul Negi Vijaya Kumar Kadappa Department of CIS University of Hyderabad India Department of MCA Vasavi College of Engineering Hyderabad India

ISBN: (纸本)9781424475421

Principal Component Analysis (PCA) is a widely accepted dimensionality reduction technique that is optimal in a MSE sense. PCA extracts `global' variations and is insensitive to `local' variations in sub patterns. Recently, we have proposed a novel approach, SubXPCA, which was more effective computationally than PCA and also effective in computing principal components with both global and local information across sub patterns. In this paper, we show the near-optimality of SubXPCA (in terms of summarization of variance) by proving analytically that `SubXPCA approaches PCA with increase in number of local principal components of sub patterns.' This is demonstrated empirically upon CMU Face Data.

关键词： Principal component analysis Eigenvalues and eigenfunctions Feature extraction Covariance matrix pattern recognition Complexity theory Electronic mail

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Evolutionary approach for approximation of artificial neural network

Evolutionary approach for approximation of artificial neural...

引用

IEEE international Advance computing conference, IACC

作者： Sangita Pal Swati Vipsita Prashanta Kumar Patra Department of Computer Science College of Engineering and Technology Bhubaneswar India Department of Computer Science National Institute of Technology Rourkela Rourkela India

ISBN: (纸本)9781424447909

Neural Network is an effective tool in the field of pattern recognition. The neural network classifies the pattern from the training data and recognizes if the testing data holds that pattern. The classical Back propagation (BP) algorithm is generally used to train the neural network for its simplicity. The basic drawback of this algorithm is its uncertainty and long training time and it searches the local optima and not the global optima. To overcome the drawback of Back propagation (BP) algorithm, here we use a hybrid evolutionary approach (GA-NN algorithm) to train neural networks. The aim of this algorithm is to find the optimized synaptic weight of neural network so as to escape from local minima and overcome the drawbacks of BP. The implementation is done taking images as input in ¿.png¿and ¿.tif¿ format.

关键词： Artificial neural networks Biological neural networks Neural networks pattern recognition Biological cells Convergence Backpropagation algorithms Computer errors Computer science Testing

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Weighted Boundary Points for Shape Analysis

Weighted Boundary Points for Shape Analysis

引用

international conference on pattern recognition

作者： Jing Zhang Rangachar Kasturi Department of Computer Science and Engineering University of South Florida USA

ISBN: (纸本)9781424475421

Shape analysis is an active and important branch in computer vision research field. In recent years, many geometrical, topological, and statistical features have been proposed and widely used for shape-related applications. In this paper, based on the properties of Distance Transform, we present a new shape feature, weight of boundary point. By computing the shortest distances between boundary points and distance contours of a transformed shape, every boundary point is assigned a weight, which contains the interior structure information of the shape. To evaluate the proposed new shape feature, we tested the weighted boundary points on shape matching and shape decomposition. The experimental results demonstrated the validity.

关键词： Shape Context Feature extraction Transforms Three dimensional displays pattern analysis Computer vision

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Gas-water flow pattern recognition by log response in horizontal wells

Gas-water flow pattern recognition by log response in horizo...

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IEEE international conference on Intelligent computing and Intelligent Systems (ICIS)

作者： Jing Lu Xiling Wu School of Geophysics and Information Engineering China University of Petroleum Beijing China Key Laboratory of Petroleum Resource and Prospecting China University of Petroleum Beijing China

Gas-water flow in horizontal development wells is complicated and changeable. In order to monitor reservoir development status and pace accurately, primary problem should be solved is to distinguish and recognize downhole gas-water flow patterns. Multi-phase flow simulative device, which is similar to downhole status, was used to conduct a series of measurement experiments using air and tap water as test media. Mixed flows were measured by real production logging tool (PLT) string at different inclinations and flow states in the transparent experimental well-bore, aim to study flow pattern recognition methods in horizontal gas wells by production logging information. Production logging experimental flow patterns analysis basing on experimental flow pattern observations and categorization reveals that gas-water mixed flow occurring in measurement procedure not only obey the general law of hydrodynamic but also own its unique characteristics resulted from logging procedure. But these experimental flow patterns still can be recognized from log response characteristics of spinner flowmeter intuitively. Cross-section water holdup vs. actual inlet water cut experiment relationship charts illustrate the links between flow parameters and flow patterns, thus they can be used to guide flow pattern recognition. The CAT 3D plots of phase profile, which are interpolation imaged by CATView software, compared with production logging experimental flow patterns suggest that gas-water flow patterns can be recognition even more intuitively by CAT 3D plots of phase profile. Combined with additional recognition method that mentioned above, more reliable flow pattern recognition results will be concluded for horizontal gas wells.

关键词： Character recognition Three dimensional displays Production Educational institutions

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CUDA Implementation of Deformable pattern recognition and its Application to MNIST Handwritten Digit Database

CUDA Implementation of Deformable Pattern Recognition and it...

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international conference on pattern recognition

作者： Yoshiki Mizukami Katsumi Tadamura Jonathan Warrell Peng Li Simon Prince Graduate School of Science and Engineering Yamaguchi University Ube Japan Department of Computing Oxford Brookes University Oxford UK Department of Computer Science University College London London UK

ISBN: (纸本)9781424475421

In this study we propose a deformable pattern recognition method with CUDA implementation. In order to achieve the proper correspondence between foreground pixels of input and prototype images, a pair of distance maps are generated from input and prototype images, whose pixel values are given based on the distance to the nearest foreground pixel. Then a regularization technique computes the horizontal and vertical displacements based on these distance maps. The dissimilarity is measured based on the eight-directional derivative of input and prototype images in order to leverage characteristic information on the curvature of line segments that might be lost after the deformation. The prototype-parallel displacement computation on CUDA and the gradual prototype elimination technique are employed for reducing the computational time without sacrificing the accuracy. A simulation shows that the proposed method with the k-nearest neighbor classifier gives the error rate of 0.57% for the MNIST handwritten digit database.

关键词： Prototypes Pixel Error analysis Mathematical model Databases Character recognition

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Monogenic Binary pattern (MBP): A Novel Feature Extraction and Representation Model for Face recognition

Monogenic Binary Pattern (MBP): A Novel Feature Extraction a...

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international conference on pattern recognition

作者： Meng Yang Lei Zhang Lin Zhang David Zhang Biometric Research Center Department of Computing Hong Kong Polytechnic University Hong Kong China

ISBN: (纸本)9781424475421

A novel feature extraction method, namely monogenic binary pattern (MBP), is proposed in this paper based on the theory of monogenic signal analysis, and the histogram of MBP (HMBP) is subsequently presented for robust face representation and recognition. MBP consists of two parts: one is monogenic magnitude encoded via uniform LBP, and the other is monogenic orientation encoded as quadrant-bit codes. The HMBP is established by concatenating the histograms of MBP of all sub-regions. Compared with the well-known and powerful Gabor filtering based LBP schemes, one clear advantage of HMBP is its lower time and space complexity because monogenic signal analysis needs fewer convolutions and generates more compact feature vectors. The experimental results on the AR and FERET face databases validate that the proposed MBP algorithm has better performance than or comparable performance with state-of-the-art local feature based methods but with significantly lower time and space complexity.

关键词： Face Histograms Face recognition Feature extraction Databases Complexity theory Filtering

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A new star identification algorithm based on fuzzy line pattern matching

A new star identification algorithm based on fuzzy line patt...

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international conference on Image and Vision computing New Zealand, IVCNZ

作者： SH. Sohrabi A.A. Beheshti Shirazi E-Iearning Center Iran University of Science and Technology Iran Electrical Engineering Iran University of Science and Technology Iran

A new star identification algorithm based on fuzzy line pattern matching is proposed for satellite attitude determination. In this algorithm, the star point pattern convert to line pattern by “Delaunay triangulation” method, then we present a fuzzy line pattern matching. In this method, we use the membership functions to describe position, orientation and relation similarities between different line segments. The simulation results based on the “Desktop Universes Star images” demonstrate that the fuzzy star pattern recognition algorithm speeds up the process of star identification and increases the rate of success greatly compared with traditional triangle matching algorithms that use the angular separations as the identification feature.

关键词： pattern matching CMOS integrated circuits

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Monocular 3D Tracking of Deformable Surfaces Using Linear Programming

Monocular 3D Tracking of Deformable Surfaces Using Linear Pr...

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international conference on pattern recognition

作者： Chenhao Wang Xiong Li Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781424475421

We present a method for 3D shape reconstruction of inextensible deformable surfaces from monocular image sequences. The key of our approach is to represent the surface as 3D triangulated mesh and formulate the reconstruction problem as a sequence of Linear Programming (LP) problems which can be effectively solved. The LP problem consists of data constraints which are 3D-to-2D keypoint correspondences and shape constraints which prevent large changes of the edge orientation between consecutive frames. Furthermore, we use a refined bisection algorithm to accelerate the computing speed. The robustness and efficiency of our approach are validated on both synthetic and real data.

关键词： Image reconstruction Three dimensional displays Surface reconstruction Shape Computer vision Linear programming Cameras

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