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IEEE International Conference on Control System, Computing and Engineering (ICCSCE)

作者： Huang, Zhiqi Guo, Jun E China Normal Univ Ctr Comp Shanghai 200062 Peoples R China

ISBN: (纸本)9781479915064;9781479915088

Support vector machine (SVM) is now widely applied in various areas for its excellent performances. For a data set, usually we use normalization method to deal with the features. However, in many cases, the value of each feature is different. Thus, SVM can't work very well. In this paper, we propose a preprocessing algorithm based on rough set (RS) theory to give different weights on each feature, which can well reflect the value of each feature. The experimental results on real data show that the proposed approach can achieve a fairly improvement of classification accuracy.

关键词： SVM preprocessing algorithm rough set feature

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KPD Based Signal preprocessing algorithm for Pulse Diagnosis

KPD Based Signal Preprocessing Algorithm for Pulse Diagnosis

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International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)

作者： Zhang, Zhichao Zhang, Yuan Jin, Wei Kos, Anton Univ Jinan Shandong Prov Key Lab Network Based Intelligent C Jinan Shandong Peoples R China Shandong Acad Chinese Med Jinan Shandong Peoples R China Univ Ljubljana Fac Elect Engn Ljubljana Slovenia

ISBN: (纸本)9781509059522

In the traditional Chinese medicine (TCM) wrist pulse diagnosis plays a major role in detecting the health status of an individual. It depends strongly on the doctors' long-term experience as well as on their different inferences. Being subjective and based on long-term experience, pulse detection methods are difficult to standardize. Kim pulse diagnosis (KPD), established by Wei Jin, is an efficient method validated by both traditional Chinese medicine and in recent years also by western medicine. The key step to automatic implementation of KPD, using signal processing and analysis, is the developed KPD signal acquisition device. However, the raw wrist pulse signal acquired from KPD device includes a significant amount of noise. This paper proposes several preprocessing algorithms for pulse diagnosis, that includes wavelet transform and Gaussian filter to remove noise and the iterative sliding window (ISW) algorithm to remove the baseline wander and split the continuous signal into single periods. Experimental results show, that the algorithm for baseline wander removal is efficient and that the segmented signal matches the signal described in KPD.

关键词： preprocessing algorithm Kim pulse diagnosis (KPD) de-noising iterative sliding window (ISW)

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Preconditioned structure-preserving Jacobi algorithms for computing the SVD of a quaternion matrix

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PHYSICA SCRIPTA 2025年第6期100卷

作者： Ma, Ru-Ru Ma, Zhicai Suzhou Univ Sci & Technol Sch Math Sci Suzhou 215009 Peoples R China Lanzhou Univ Technol Sch Sci Lanzhou 730050 Peoples R China

The singular value decomposition (SVD) of quaternion matrices is a cornerstone of color image compression. However, existing computational methods for quaternion SVD remain inefficient, often lacking the speed and scalability required for real-world applications. To address this challenge, we introduce two novel preconditioned structure-preserving Jacobi algorithms designed to compute the SVD of quaternion matrices efficiently. Central to our approach is the use of quaternion rank-revealing QR (QRRQR) factorization as a preprocessing step, which serves as a robust dimension reduction strategy for both one-sided and two-sided Jacobi methods. Notably, we rigorously analyze the off-diagonal structure of the upper triangular matrix generated by QRRQR, a key innovation that enables significant acceleration of the two-sided Jacobi algorithm. By exploiting this structural property, we effectively reduce computational overhead while preserving numerical stability. Extensive numerical experiments validate the superior efficiency, accuracy, and scalability of our algorithms compared to some conventional approaches, demonstrating their potential for practical deployment in large-scale color image processing tasks.

关键词： quaternion SVD structure-preserving Jacobi method rank revealing QR preprocessing algorithm

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Effective statistical-based and dynamic fingerprint preprocessing technique

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IET BIOMETRICS 2017年第1期6卷 9-18页

作者： Iloanusi, Ogechukwu N. Univ Nigeria Dept Elect Engn Fac Engn Nsukka 410001 Enugu State Nigeria

Challenges to contextual filtering techniques include difficulties in estimating orientation field in poor quality images and subsequently failure to extract ridges reliably in large regions of low quality. This study proposes a statistical-based and dynamic fingerprint preprocessing technique for adaptive contrast enhancement and binarisation of fair and poor qualities plain and rolled fingerprints with large regions of low quality, prior to orientation field estimation. The algorithm effectively enhances smudged and faded ridges uniformly in recoverable regions, based on values of statistical variables computed locally in each region. The preprocessing algorithm employs a locally adaptive thresholding approach resulting in enhanced binarised images. The performance of the proposed algorithm was determined by carrying out biometric verification evaluation using a popular commercial biometric matching software, on databases of fingerprints in their original forms, as well as same fingerprints enhanced with the proposed algorithm. Experiments show that fingerprints are uniformly enhanced and binarised;and smudged or faded ridges in recoverable regions made visible. Fingerprint verification evaluation on preprocessed fingerprints resulted in lower error rates in 12 databases. These results show that the proposed algorithm significantly improves recognition.

关键词： fingerprint identification statistical analysis image enhancement image segmentation image matching image filtering dynamic fingerprint preprocessing technique statistical-based fingerprint preprocessing technique contextual filtering techniques adaptive contrast enhancement plain fingerprints rolled fingerprints orientation field estimation faded ridges smudged ridges recoverable regions statistical variables preprocessing algorithm locally adaptive thresholding enhanced binarised images biometric verification evaluation commercial biometric matching software

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preprocessing method for robust topography reconstruction of surfaces of metal additive manufactured parts based on focus variation microscopy

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TM-TECHNISCHES MESSEN 2024年第5期91卷 233-242页

作者： Xu, Xin Pahl, Tobias Serbes, Hueseyin Krooss, Philipp Niendorf, Thomas Lehmann, Peter Univ Kassel Fachgebiet Messtechn FB16 Elektrotech Informat Kassel Germany Univ Kassel Inst Werkstofftechn Fachgebiet Met Werkstoffe FB15 Maschinenbau Kassel Germany

When using an areal measuring optical instrument to measure rough surfaces, especially surfaces generated by metal additive manufacturing (e.g. laser and electron beam powder bed fusion), topographical artifacts such as spikes on a reconstructed surface are nearly unavoidable. These artifacts may affect the determination of surface roughness parameters and lead to erroneous surface features. This paper proposes a new preprocessing method to eliminate most artifacts before extracting surface heights of rough surfaces measured by focus variation microscopy. In this method, the axial region where a surface height value is located with the highest probability is estimated, based on datasets of planes parallel to the axial scanning direction. Results regarding height measurements with and without the preprocessing method are compared by measuring a Rubert Microsurf 329 comparator test panel for reference and workpieces produced by metal additive manufacturing.

关键词： focus variation microscopy outlier elimination preprocessing algorithm 3D profilometry roughness measurement metal additive manufacturing

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An image preprocessing method for kidney stone segmentation in CT scan images

An image preprocessing method for kidney stone segmentation ...

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Joint International Conference on Computer Engineering, Network and Intelligent Multimedia (CENIM) / 11th AUN/SEED-Net Regional Conference on Computer and Information Engineering (RCCIE)

作者： Thein, Nilar Nugroho, Hanung Adi Adji, Teguh Bharata Hamamoto, Kazuhiko Univ Gadjah Mada Dept Elect Engn & Informat Technol Yogyakarta Indonesia Tokai Univ Dept Informat Media Technol Tokyo Japan

ISBN: (纸本)9781538675090

In 3D medical imaging, anatomical and other structures such as kidney stones are often identified and extracted with the aid of diagnosis and assessment of disease. Automatic kidney stone segmentation from abdominal CT images is challenging on the aspects of segmentation accuracy due to its variety of size, shape and location. The performance of 3D organ segmentation algorithm is also degraded by the image complexity containing multiple organs and because of their huge size. The current need is a preprocessing algorithm to assist the segmentation process. The objective of the present study was to develop reader independent preprocessing algorithm for kidney stone detection and segmentation in CT images. Three thresholding algorithms based on intensity, size and location are applied for unwanted regions removing such as soft-organ removing, bony skeleton removing and bed-mat removing. The digitized transverse abdomen CT scans images from 30 patients with kidney stone cases were included in statistical analysis and validation. As validation data for analysis, the estimation of coordinate points in stone region was measured independently by expert radiology. Experimental results prove that the proposed preprocessing algorithm has 95.24% sensitivity as the evaluation parameter. So, it can reduce the noise and unwanted regions in each procedure with good detection.

关键词： preprocessing algorithm kidney stone detection unwanted regions removing

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Automatic preprocessing Scheme for Real-Time Digital Simulation

Automatic Preprocessing Scheme for Real-Time Digital Simulat...

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53rd Annual Meeting of the IEEE-Industry-Applications-Society (IAS)

作者： Noh, Hyeokjin Lee, Byongjun Song, Jiyoung Lee, Chulkyun Korea Univ Sch Elect Engn Seoul South Korea Korea Elect Power Coporat Korea Elect Power Res Inst Daejeon South Korea LSIS Co Ltd HVDC Syst Res Team Anyang South Korea

ISBN: (纸本)9781538645369

This paper presents the data preprocessing algorithm for real time digital simulation of large power systems based on energy management system data. Recently, the power systems have become complicated due to increase of distributed power, including renewable energy and High Voltage Direct Current & Flexible AC Transmission System. In order to overcome the technological limitations, there are more and more cases of analyzing real time operation characteristics through Real-Time Digital Simulator. However, because the Real-Time Digital Simulator has a load unit limit per rack, it is difficult to simulate large scale power systems. When analyzing large scale power systems, we often use data obtained from actual power system operation data through Energy Management System. In this paper, we propose a solution to solve various errors and reduce the load unit limit for real time digital simulation by processing Energy Management System data.

关键词： preprocessing algorithm Large Scale Power Systems Energy Management System Real Time Digital Simulator Python

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Computational enhancements of continuous production scheduling MILPs using tightening constraints

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COMPUTERS & CHEMICAL ENGINEERING 2024年 184卷

作者： Samadi, Amin Maravelias, Christos T. Princeton Univ Dept Chem & Biol Engn Princeton NJ 08540 USA Princeton Univ Andlinger Ctr Energy & Environm Princeton NJ 08540 USA

In this paper, we propose employing tightening constraints, based on known system information, into discretetime continuous production scheduling models to enhance their computational performance. We first establish a model with transient operations such as startups, shutdowns, and direct transitions. We propose a demand propagation algorithm (DPA), implemented as a preprocessing step, that utilizes demand information and other known system parameters to calculate parameters which are later used in a series of constraints to tighten the feasible space of the linear programming (LP) relaxation of the mixed-integer linear programming (MILP) problem. This reduces the branching required to close the optimality gap which consequently decreases solution times. We present computational results that show our proposed method can lead to over an order of magnitude reduction in solution times.

关键词： Discrete -time Continuous processes preprocessing algorithm Bound propagation

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A pre-processing technique to decrease inspection time in glass tube production lines

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IET IMAGE PROCESSING 2021年第10期15卷 2179-2191页

作者： De Vitis, Gabriele Antonio Foglia, Pierfrancesco Prete, Cosimo Antonio Univ Pisa Dipartimento Ingn Informaz Via Diotisalvi 2 I-56100 Pisa Italy

In case of glass tube for pharmaceutical applications, high-quality defect detection is made via inspection systems based on computer vision. The processing must guarantee real-time inspection and meet increasing rate and quality requirements. Defect detection in glass tubes is complicated by aspects that hamper the efficiency of state-of-the-art techniques. This paper presents a pre-processing algorithm which excludes portions of the image where defects are surely absent. The approach decreases the time for defect detection and classification phases (any detection algorithm can be applied), as they are applied only in high-probability candidate sub-image. We derive a methodology to get robust values of algorithm's parameters during production. The algorithm relies on detrended standard deviation and double threshold hysteresis, which solve issues related to the misalignment between illuminator and acquisition camera, and enable a robust detection despite rotation, vibration, and irregularities of tubes. We consider Canny, MAGDDA, and Niblack algorithms. The solution keeps the detection quality of such algorithms and reaches a 4.69x throughput gain. It represents a methodology to obtain defect detection in time-constrained environments through a software-only approach, and can be exploited in parallel/accelerated solutions and in contexts where a linear camera is utilized on both flat and uneven surfaces.

关键词： robust detection detection algorithm time constrained environments probability quality requirements high probability candidate subimage automatic optical inspection preprocessing technique image sensors Niblack algorithms glass products inspection systems production engineering computing high quality defect detection preprocessing algorithm computer vision inspection time glass tube production lines image coding detection quality quality control real-time inspection

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Fractal dimension based on Minkowski-Bouligand method using exponential dilations

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ELECTRONICS LETTERS 2015年第6期51卷 475-476页

作者： Luppe, M. EESC USP Lab Microsistemas Dept Engn Eletr & Comp Sao Carlos SP Brazil

The fractal dimension (FD) is an important feature used for classification and shape recognition. The best method to obtain the FD is the Bouligand-Minkowski method. However, this method is computationally exhaustive because of the use of the distance transform. Presented is a modification in the method and a proposed architecture, suitable for field programmable gate array implementation that enables calculating the FD in a simple and efficient way.

关键词： optical projectors image processing micro-optomechanical devices micromirrors interpolation efficient nonlinear geometric distortion correction scanned laser pico projectors laser light sources microelectromechanical systems MEMS mirror devices image distortion nonlinear mirror driving methods preprocessing algorithm blockwise homography transforms backward blockwise homography transforms distortion-free images bilinear interpolations

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