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A novel robust automated FFT-based segmentation and features selection algorithm for acoustic emission condition based monitoring systems

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APPLIED ACOUSTICS 2015年第0期88卷 66-74页

作者： Gowid, Samer Dixon, Roger Ghani, Saud Univ Loughborough Fac Engn Sch Elect Elect & Syst Engn Loughborough Leics England Qatar Univ Coll Engn Dept Mech & Ind Engn Doha Qatar

This paper aims at developing a robust, fast-response and automated FFT-based features selection algorithm for the development of acoustic emission practical condition based monitoring applications of mechanical systems. Further scope of this work is to investigate the suitability of acoustic emission for the fault diagnostic of high speed centrifugal equipment using a single AE sensor. Experiments were conducted using an industrial air blower system with a rotational speed of 15,650 RPM. Five experiments for five different machine conditions were carried out. Ten data sets were collected for each machine condition with a total number of 50 data sets. Fifty percent of the data sets were used for training and the remaining data sets were used for verification. Tailor made programs for spectral features selection and for classification of faults were developed using Maltab to implement the proposed algorithm to an industrial air blower system. The results showed the suitability of the acoustic emission spectral features technique for the fault diagnostic of centrifugal equipment and proved the effectiveness and competitiveness of the proposed automated features selection algorithm. The sets of features selected by the algorithm yielded a detection accuracy of 100%. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Condition based monitoring segmentation algorithm Features selection Centrifugal equipment and fault detection

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segmentation of pomegranate MR images using spatial fuzzy c-means (SFCM) algorithm

Segmentation of pomegranate MR images using spatial fuzzy c-...

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International Conference on Graphic and Image Processing (ICGIP)

作者： Moradi, Ghobad Shamsi, Mousa Sedaaghi, M. H. Alsharif, M. R. Sahand Univ Technol Fac Elect Engn Tabriz Iran Univ Ryukyus Fac Elect Engn Okinawa Japan

ISBN: (纸本)9780819489326

segmentation is one of the fundamental issues of image processing and machine vision. It plays a prominent role in a variety of image processing applications. In this paper, one of the most important applications of image processing in MRI segmentation of pomegranate is explored. Pomegranate is a fruit with pharmacological properties such as being anti-viral and anti-cancer. Having a high quality product in hand would be critical factor in its marketing. The internal quality of the product is comprehensively important in the sorting process. The determination of qualitative features cannot be manually made. Therefore, the segmentation of the internal structures of the fruit needs to be performed as accurately as possible in presence of noise. Fuzzy c-means (FCM) algorithm is noise-sensitive and pixels with noise are classified inversely. As a solution, in this paper, the spatial FCM algorithm in pomegranate MR images' segmentation is proposed. The algorithm is performed with setting the spatial neighborhood information in FCM and modification of fuzzy membership function for each class. The segmentation algorithm results on the original and the corrupted Pomegranate MR images by Gaussian, Salt Pepper and Speckle noises show that the SFCM algorithm operates much more significantly than FCM algorithm. Also, after diverse steps of qualitative and quantitative analysis, we have concluded that the SFCM algorithm with 5x5 window size is better than the other windows.

关键词： Image processing pomegranate MR images segmentation algorithm spatial fuzzy c-means clustering

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Feasibility of a semi-automated contrast-oriented algorithm for tumor segmentation in retrospectively gated PET images: phantom and clinical validation

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PHYSICS IN MEDICINE AND BIOLOGY 2015年第24期60卷 9227-9251页

作者： Carles, Montserrat Fechter, Tobias Nemer, Ursula Nanko, Norbert Mix, Michael Nestle, Ursula Schaefer, Andrea Univ Hosp Freiburg Dept Radiat Oncol D-79106 Freiburg Germany Univ Hosp Freiburg Dept Nucl Med D-79106 Freiburg Germany Univ Saarland Dept Nucl Med Med Ctr D-66421 Homburg Germany

PET/CT plays an important role in radiotherapy planning for lung tumors. Several segmentation algorithms have been proposed for PET tumor segmentation. However, most of them do not take into account respiratory motion and are not well validated. The aim of this work was to evaluate a semi-automated contrast-oriented algorithm (COA) for PET tumor segmentation adapted to retrospectively gated (4D) images. The evaluation involved a wide set of 4D-PET/CT acquisitions of dynamic experimental phantoms and lung cancer patients. In addition, segmentation accuracy of 4D-COA was compared with four other state-of-the-art algorithms. In phantom evaluation, the physical properties of the objects defined the gold standard. In clinical evaluation, the ground truth was estimated by the STAPLE (Simultaneous Truth and Performance Level Estimation) consensus of three manual PET contours by experts. algorithm evaluation with phantoms resulted in: (i) no statistically significant diameter differences for different targets and movements (Delta phi = 0.3 +/- 1.6 mm);(ii) reproducibility for heterogeneous and irregular targets independent of user initial interaction and (iii) good segmentation agreement for irregular targets compared to manual CT delineation in terms of Dice Similarity Coefficient (DSC = 0.66 +/- 0.04), Positive Predictive Value (PPV = 0.81 +/- 0.06) and Sensitivity (Sen. = 0.49 +/- 0.05). In clinical evaluation, the segmented volume was in reasonable agreement with the consensus volume (difference in volume (% Vol) = 40 +/- 30, DSC = 0.71 +/- 0.07 and PPV = 0.90 +/- 0.13). High accuracy in target tracking position (Delta ME) was obtained for experimental and clinical data (Delta MEexp = 0 +/- 3 mm;Delta MEclin= 0.3 +/- 1.4 mm). In the comparison with other lung segmentation methods, 4D-COA has shown the highest volume accuracy in both experimental and clinical data. In conclusion, the accuracy in volume delineation, position tracking and its robustness on highly irregular

关键词： segmentation algorithm 4D-PET/CT radiotherapy dynamic phantoms lung cancer

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Image Tracking and segmentation algorithms Based on Laser Sensors and Wireless Network Devices in Sports Target Detection

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MOBILE NETWORKS & APPLICATIONS 2024年

作者： Liu, Hong Teacher Dev Ctr Liuhe Dist Off Educ Sci Res Nanjing Jiangsu Peoples R China

This paper aims to discuss the application of image tracking and segmentation algorithm based on laser sensor and wireless network equipment in moving object detection. Traditional target detection methods have problems in dynamic environment. Therefore, we propose a new integrated method, which combines the high-precision detection ability of laser sensor and the real-time data transmission advantage of wireless sensor network to improve the accuracy and response speed of moving target detection. A laser sensor is used to capture the 3D position information of the target, and an image processing algorithm is used for real-time tracking and segmentation. The acquired data is transmitted wirelessly to a central server for further analysis and processing. A network consisting of multiple wireless sensor nodes is constructed to test the detection performance under different environmental conditions. The results show that the combination of laser sensor and wireless network can significantly improve the detection rate and tracking accuracy of moving targets. Compared with traditional methods, our new algorithm also shows good performance in response time and data transmission efficiency.

关键词： Laser sensor Wireless network equipment Image tracking segmentation algorithm Moving object detection

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A Strategy of Parallel Seed-Based Image segmentation algorithms for Handling Massive Image Tiles over the Spark Platform

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REMOTE SENSING 2021年第10期13卷 1969-1969页

作者： Chen, Fang Wang, Ning Yu, Bo Qin, Yuchu Wang, Lei Chinese Acad Sci Aerosp Informat Res Inst Key Lab Digital Earth Sci 9 Dengzhuang South Rd Beijing 100094 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Aerosp Informat Res Inst State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China Chinese Acad Sci Aerosp Informat Res Inst Hainan Key Lab Earth Observat Sanya 572029 Peoples R China

The volume of remote sensing images continues to grow as image sources become more diversified and with increasing spatial and spectral resolution. The handling of such large-volume datasets, which exceed available CPU memory, in a timely and efficient manner is becoming a challenge for single machines. The distributed cluster provides an effective solution with strong calculation power. There has been an increasing number of big data technologies that have been adopted to deal with large images using mature parallel technology. However, since most commercial big data platforms are not specifically developed for the remote sensing field, two main issues exist in processing large images with big data platforms using a distributed cluster. On the one hand, the quantities and categories of official algorithms used to process remote sensing images in big data platforms are limited compared to large amounts of sequential algorithms. On the other hand, the sequential algorithms employed directly to process large images in parallel over a distributed cluster may lead to incomplete objects in the tile edges and the generation of large communication volumes at the shuffle stage. It is, therefore, necessary to explore the distributed strategy and adapt the sequential algorithms over the distributed cluster. In this research, we employed two seed-based image segmentation algorithms to construct a distributed strategy based on the Spark platform. The proposed strategy focuses on modifying the incomplete objects by processing border areas and reducing the communication volume to a reasonable size by limiting the auxiliary bands and the buffer size to a small range during the shuffle stage. We calculated the F-measure and execution time to evaluate the accuracy and execution efficiency. The statistical data reveal that both segmentation algorithms maintained high accuracy, as achieved in the reference image segmented in the sequential way. Moreover, generally the strategy took le

关键词： segmentation algorithm distributed computation image processing spark platform digital disaster reduction

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Knowledge Automatic Indexing Based on Concept Lexicon and Segm-entation algorithm

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Journal of Donghua University(English Edition) 2005年第1期22卷 26-30页

作者：王兰成蒋丹乐嘉锦 College of Information Science and Technology Donghua University Shanghai 200051Department of Information Management Shanghai Political College PLA Shanghai 200433 College of Mechanical Engineering Shanghai Jiaotong University Shanghai 200030 College of Information Science and Technology Donghua University Shanghai 200051

This paper is based on two existing theories about automatic indexing of thematic knowledge concept. The prohibit-word table with position information has been designed. The improved Maximum Matching-Minimum Backtracking method has been researched. Moreover it has been studied on improved indexing algorithm and application technology based on rules and thematic concept word table.

关键词： Concept Lexicon segmentation algorithm Knowledge Indexing.

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A particle shape-based segmentation method to characterize spray dried materials by X-Ray microtomography

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Particuology 2023年第10期81卷 119-127页

作者： Nora Alina Ruprecht Heike Teichmann Reinhard Kohlus University of Hohenheim Institute of Food Science and BiotechnologyDepartment of Process Engineering and Food PowdersGarbenstr.2570599StuttgartGermany

For accurate description of particle structure,single particle properties are required so that the properties of interest can be expressed as distributed parameters.X-Ray microtomography of the powder bed with subsequent particle separation can be used for this *** this paper,a new algorithm for X-Ray microtomography images of spray dried particles was introduced since standard methods tend to fail if the particle size distribution is *** algorithm is based on 2D shape classification and subsequent 3D reconstitution of the particle using only a shape classifier as free *** proposed algorithm was validated *** the algorithm,single particle porosities were obtained,which ranged from 0 to 70%.Prerequisites for the application of the algorithm are that a shape classifier can be set and that the 3D shape is regular.

关键词： Spray drying Particle structure X-Ray microtomography segmentation algorithm Porosity distribution

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An Improved Volume Rendering algorithm Based on Voxel segmentation

An Improved Volume Rendering Algorithm Based on Voxel Segmen...

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2012 IEEE International Conference on Computer Science and Automation Engineering（CSAE 2012）

作者： Zi-Ming Zhang,Wang Lu College of Electronic Information and Control Engineering Beijing University of Technology Beijing,the People's Republic of China Yuan-Zheng Shi,Ting-Lei Yang,Shu-Li Liang College of Electronic Information and Control Engineering Beijing University of Technology Beijing,the People's Republic of China

Volume rendering could display the image in an integrated distribution of a variety of *** is convenient to view the body data for a *** rendering should traverse each voxel of the data,causing large calculation and slow image generation,and can not change the external light and *** is need to start the drawing again when parameters have *** complex process lead the slow speed of *** this paper,volume rendering algorithm based on segmentation in three-dimensional reconstruction is present,including the segmentation of CT data,the normal vector of the volume element,and the generation of the final *** method greatly accelerated the speed of rendering image,and improves image display ***,it can well reflect the global status of three- dimensional data.

关键词： Signal and information processing Volume rendering three-dimensional reconstruction segmentation algorithm

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Representative Segment-Based Emotion Analysis and Classification with Automatic Respiration Signal segmentation

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IEEE TRANSACTIONS ON AFFECTIVE COMPUTING 2012年第4期3卷 482-495页

作者： Wu, Chi-Keng Chung, Pau-Choo (Julia) Wang, Chi-Jen Natl Cheng Kung Univ Dept Elect Engn Inst Comp & Commun Engn Tainan 70101 Taiwan Natl Cheng Kung Univ Dept Elect Engn Tainan 70101 Taiwan Natl Cheng Kung Univ Dept Nursing Tainan 70101 Taiwan

Human respiration has been reported as having great relevance to the emotional state. However, the respiration signal obtained using traditional biosensors not only reflects changing emotions and emotion intensities, but also contains motion artifacts. The resulting information ambiguity limits the practical application of the respiration signal as a means of reliable affective state appraisal. Thus, the present study proposes a method for extracting representative Emotion Elicited Segments (EESs) from the respiration signal such that the affective state of the individual can be more reliably determined. The EES extraction process involves the combination of the following procedures, namely, 1) Mutual Information-Based Emotion Relevance Feature Ranking based on the Dynamic Time Warping Distance (MIDTW), and 2) Constraint-based Elicited Segment Density (CESD) analysis. Due to the innate regularity of the respiration signal, the respiration pattern under a particular emotional state would be relatively quasihomogeneous over time. Accordingly, a parameter-free Respiration quasi-Homogeneity segmentation (RHS) algorithm is proposed for partitioning the respiration signal into quasi-homogenous segments from which the EESs can then be extracted. The experimental results obtained for five prototypical emotions (i.e., "love," "sadness," "joy," "anger," and "fear") show that the proposed segmentation/extraction methodology enables the EESs to be reliably identified and yields an average classification rate of 88 percent.

关键词： segmentation algorithm motion artifacts emotion classification dynamic time-warping mutual information constraint-based clustering analysis

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Optimal matrix-segmentation by rectangles

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DISCRETE APPLIED MATHEMATICS 2009年第9期157卷 2015-2030页

作者： Engel, Konrad Univ Rostock Inst Math D-18051 Rostock Germany

We study the problem of decomposing a nonnegative matrix into a nonnegative combination of 0-1-matrices whose ones form a rectangle such that the sum of the coefficients is minimal. We present for the case of two rows an easy algorithm that provides an optimal solution which is integral if the given matrix is integral. An additional integrality constraint makes the problem more difficult if the matrix has more than two rows. An algorithm that is based on the revised simplex method and uses only very few Gomory cuts yields exact integral solutions for integral matrices of reasonable size in a short time. For matrices of large dimension we propose a special greedy algorithm that provides sufficiently good results in numerical experiments. (C) 2008 Elsevier B.V. All rights reserved.

关键词： Network flow Intensity-modulated radiation therapy (IMRT) segmentation algorithm Linear programming Rectangular partition Matrix-decomposition Gomory cut Revised simplex method

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