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Robust single-object image segmentation based on salient transition region

PATTERN RECOGNITION 2016年 52卷 317-331页

作者： Li, Zuoyong Liu, Guanghai Zhang, David Xu, Yong Minjiang Univ Dept Comp Sci Fuzhou 350108 Peoples R China Guangxi Normal Univ Sch Comp Sci & Informat Technol Guilin 541004 Peoples R China Hong Kong Polytech Univ Dept Comp Biometr Res Ctr Kowloon Hong Kong Peoples R China Harbin Inst Technol Shenzhen Grad Sch Biocomp Res Ctr Shenzhen 518055 Peoples R China

Existing transition region-based image thresholding methods are unstable, and fail to achieve satisfactory segmentation accuracy on images with overlapping gray levels between object and background. This is because they only take the gray level mean of pixels in transition regions as the segmentation threshold of the whole image. To alleviate this issue, we proposed a robust hybrid single-object image segmentation method by exploiting salient transition region. Specifically, the proposed method first uses local complexity and local variance to identify transition regions of an image. Secondly, the transition region with the largest pixel number is chosen as salient transition region. Thirdly, a gray level interval is determined by using transition regions and image information, and one gray level of the interval is determined as the segmentation threshold by using the salient transition region. Finally, the image thresholding result is refined as final segmentation result by using the salient transition region to remove fake object regions. The proposed method has been extensively evaluated by experiments on 170 single object real world images. Experimental results show that the proposed method achieves better segmentation accuracy and robustness than several types of image segmentation techniques, and enjoys its nature of simplicity and efficiency. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： local complexity local variance Salient transition region Image thresholding Image segmentation

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PVO-Based Reversible Data Hiding Using Global Sorting and Fixed 2D Mapping Modification

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2024年第1期34卷 618-631页

作者： Wu, Yuhong Hu, Runwen Xiang, Shijun Jinan Univ Coll Informat Sci & Technol Guangzhou 510632 Peoples R China

Pixel-value-ordering (PVO) is one of the most popular methods in reversible data hiding (RDH). In PVO based methods, pixels are processed in a block-wise way, so that the local similarities of the images are considered but the global statistical characteristics are ignored. To better utilize the correlations of pixels, this paper proposes a global sorting strategy to combine utilizations of local and global characteristics of the images. For each pixel, its prediction value and local complexity are first calculated based on its local characteristics. Then the image pixels are sorted globally according to their prediction values to generate a single-sorted pixel sequence, in which the pixels with the equal prediction values are sorted again by referring to their local complexities. In such a way, the spatial distances of image pixels are broken so that the global statistical characteristics can be well exploited. With the proposed sorting strategy, we can obtain a more regular 2D histogram by segmenting the sorted sequence for the location-based PVO (LPVO) predictor. Owe to the regular 2D histogram, we have designed an efficient 2D mapping to achieve perfect performance for all the tested images. With the proposed RDH scheme, the PSNR of the image Lena is as high as 61.86 dB and the average PSNR of the Kodak dataset reaches 63.55 dB after embedding 10,000 bits. The superiority of the proposed method has been verified by comparing with recent state-of-the-art RDH methods.

关键词： Sorting complexity theory Histograms Distortion Correlation Prediction algorithms Image coding Reversible data hiding pixel-value-ordering global sorting prediction value local complexity

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Using the doubling dimension to analyze the generalization of learning algorithms

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JOURNAL OF COMPUTER AND SYSTEM SCIENCES 2009年第6期75卷 323-335页

作者： Bshouty, Nader H. Li, Yi Long, Philip M. Google Mountain View CA 94043 USA Technion Israel Inst Technol IL-32000 Haifa Israel Genome Inst Singapore Singapore Singapore

Given a set F of classifiers and a probability distribution over their domain. one call define a metric by taking the distance between a pair of classifiers to be the probability that they classify a random item differently. We prove bounds on the sample complexity of PAC learning in terms of the doubling dimension of this metric. These bounds imply known bounds on the sample complexity of learning halfspaces with respect to the uniform distribution that are optimal up to a constant factor. We then prove a bound that holds for any algorithm that outputs a classifier with zero error whenever this is possible;this bound is in terms of the maximum of the doubling dimension and the VC-dimension of F and strengthens the best known bound in terms of the VC-dimension alone. Finally, we show that there is no bound on the doubling dimension of halfspaces in R-n in terms of n that holds independently of the domain distribution. This implies that there is no such a bound in terms of the VC-dimension of F (in contrast with the metric dimension). (C) 2009 Elsevier Inc. All rights reserved.

关键词： PAC learning Generalization Doubling dimension Doubling metric Learning theory Statistical learning theory local complexity

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Assouad Spectrum Thresholds for Some Random Constructions

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CANADIAN MATHEMATICAL BULLETIN-BULLETIN CANADIEN DE MATHEMATIQUES 2020年第2期63卷 434-453页

作者： Troscheit, Sascha Univ Vienna Fac Math Oskar Morgenstern Pl 1 A-1090 Vienna 1090 Austria

The Assouad dimension of a metric space determines its extremal scaling properties. The derived notion of the Assouad spectrum fixes relative scales by a scaling function to obtain interpolation behaviour between the quasi-Assouad and the box-counting dimensions. While the quasiAssouad and Assouad dimensions often coincide, they generally differ in random constructions. In this paper we consider a generalised Assouad spectrum that interpolates between the quasi-Assouad and the Assouad dimension. For common models of random fractal sets, we obtain a dichotomy of its behaviour by finding a threshold function where the quasi-Assouad behaviour transitions to the Assouad dimension. This threshold can be considered a phase transition, and we compute the threshold for the Gromov boundary of Galton-Watson trees and one-variable random self-similar and self-affine constructions. We describe how the stochastically self-similar model can be derived from the Galton-Watson tree result.

关键词： Assouad dimension local complexity Gallon-Watson process stochastic self-similarity

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An Approach to Measuring complexity Within the Boundaries of a Natural Language Fuzzy Grammar 15th

An Approach to Measuring Complexity Within the Boundaries of...

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15th International Conference on Distributed Computing and Artificial Intelligence

作者： Torrens Urrutia, Adria Univ Rovira & Virgili Tarragona Spain

ISBN: (纸本)9783319996080

This paper presents an approach to evaluate complexity by means of a Natural Language Fuzzy Grammar. Frequently, Linguistics has described a natural language grammar by means of discrete terms. However, a grammar can be explained in terms of degrees by following the concepts of linguistic gradience & fuzziness. Understanding a grammar as a fuzzy or gradient object allows us to establish degrees of grammaticality for every linguistic input. This shall be meaningful for linguistic complexity considering that the less grammatical an input is the more complex its processing will be. From this regard, an input's degree of complexity is always going to depend on its grammar. The bases of the natural language fuzzy grammar are shown here. Some of these are described by Fuzzy Type Theory. The linguistic inputs are characterized by constraints through a Property Grammar.

关键词： Degrees of grammaticality Degrees of complexity Fuzzy grammar local complexity Syntax

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Segmentation of Coronary Arteries Based on Transition Region Extraction

Segmentation of Coronary Arteries Based on Transition Region...

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2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR)

作者： Kang, Wenwei Wang, Ke Chen, Wanzhong Li, Yong Jilin Univ Coll Commun Engn Changchun Jilin Prov Peoples R China Jilin Teachers Inst Engn Technol Coll Informat Engn Changchun Jilin Prov Peoples R China

ISBN: (纸本)9781424451944

Aiming at the complex background of coronary angiograms, weak contrast between the coronary arteries and the background, a new segmentation method based on transition region extraction is proposed. The paper analyzes the characteristic of coronary angiograms, and then 6 different Gaussian matched templates are used to enhance the coronary angiograms. Finally, the coronary arteries are obtained with local complexity method based on transition region extraction. The experiments indicate that the proposed method outperforms the segmentation method based on top-hat about the small vessels extraction, connectivity and effectiveness. The method is indeed valuable for diagnosis and the quantitative analysis of coronary arteries.

关键词： coronary angiogram Gaussian filtering local complexity transition region

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The Segmentation Method Based on Fusion Algorithm of Transition Region Extraction for Coronary Angiograms

The Segmentation Method Based on Fusion Algorithm of Transit...

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2nd International Conference on Advanced Engineering Materials and Technology (AEMT)

作者： Kang, Wenwei Kang, Xiaotao Liu, Bin Jilin Univ Coll Commun Engn Changchun 130023 Jilin Province Peoples R China

ISBN: (纸本)9783037854488

Aiming at the complex background of coronary angiograms, weak contrast between the coronary arteries and the background, a new segmentation method based on transition region extraction is proposed. Firstly, the coronary arteries are extracted by using the local complexity method based on Top-hat. Then the coronary arteries are extracted again by using the local complexity method based on Gaussian filter. Finally, the segmentation image is obtained by fusing two extracted coronary arteries images. The experiments indicate that the proposed method has better performance on the small vessels extraction and background elimination. In addition, the method is valuable for diagnosis and the quantitative analysis of vessels.

关键词： Coronary angiogram Top-hat Gaussian filtering local complexity Transition region

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complexity Analysis of Root Clustering for a Complex Polynomial 16

Complexity Analysis of Root Clustering for a Complex Polynom...

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41st ACM International Symposium on Symbolic and Algebraic Computation (ISSAC)

作者： Becker, Ruben Sagraloff, Michael Sharma, Vikram Xu, Juan Yap, Chee MPI Informat Saarbrucken Grad Sch Comp Sci Saarbrucken Germany MPI Informat Saarbrucken Germany Inst Math Sci Madras Tamil Nadu India NYU Courant Inst Math Sci New York NY USA

ISBN: (纸本)9781450343800

Let F(z) be an arbitrary complex polynomial. We introduce the local root clustering problem, to compute a set of natural s-clusters of roots of F(z) in some box region Bo in the complex plane. This may be viewed as an extension of the classical root isolation problem. Our contribution is twofold: we provide an efficient certified subdivision algorithm for this problem, and we provide a bit-complexity analysis based on the local geometry of the root clusters. Our computational model assumes that arbitrarily good approximations of the coefficients of F are provided by means of an oracle at the cost of reading the coefficients. Our algorithmic techniques come from a companion paper [3] and are based on the Pellet test, Graeffe and Newton iterations, and are independent of Schonhage's splitting circle method. Our algorithm is relatively simple and promises to be efficient in practice.

关键词： root isolation Graeffe iteration root clustering pellet test complexity of roots newton method local complexity root finding

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An improved adaptive surrogate model and application in thermal management system design

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MATERIALS & DESIGN 2021年 208卷

作者： Xu, Huanwei Li, Hao Xiang, Ge Zhang, Xin Univ Elect Sci & Technol China Sch Mech & Elect Engn Chengdu 611731 Peoples R China

It is time-consuming to obtain the responses of real or high-precision simulation models in complex engineering problems. The surrogate model based on sample points can approximate the real model and thus greatly reduce the computational effort. The selection of sample points has a great influence on the accuracy of the surrogate model. Aiming at the problem of sample point selection in the process of establishing surrogate model, an adaptive sampling method based on distance density and local complexity is proposed. In this method, distance density is used to quantify the sparsity of new sample points, and local complexity is applied to quantify the change complexity of response values near new sample points. The high-quality of new sample point is added to improve the accuracy of the surrogate model. This method is compared with two other classical adaptive sampling methods through nine test functions. The results show that this method can make the new sample point more distributed in the key area of sample space, so that fewer sample points are used to establish a high-precision surrogate model. Finally, the effectiveness of this method is verified through an optimization of the thermal management system design for liquid-cooled cylindrical batteries. (C) 2021 The Authors. Published by Elsevier Ltd.

关键词： Surrogate model Adaptive sampling Distance density local complexity Thermal management system design

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The Scale-rate as a Novel Feature of complexity for Digital Images

The Scale-rate as a Novel Feature of Complexity for Digital ...

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2010 International Conference on Intelligent Computation Technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

作者： Jipeng Du Yanming Gao Bo Wang Li Zhang Meng Tan North China Sea Information Center North China Sea Branch of the State Oceanic Administration No. 22 Fushun Road Qingdao Shandong 266033 China

The scale-rate is presented as the measurement of local complexity for digital images and signals, which is proved to be a feature of local edge area in images. The multi-feature edge detection and automatic moving vehicle detection are implemented. The experimental results indicate the effectiveness of the proposed methods.

关键词： scale-rate local complexity multi-feature edge detection video segmentation traffic surveillance

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