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2007 8th International Conference on Electronic Measurement & Instruments（ICEMI’2007）

作者： Tan Xuping (Electronic Information Depar.of Guangdong Agriculture-Industry-Business Polytechnic College Yue Ken Road 198 Guangzhou 510507 China)

In ultrasonic imaging system,the system to distinguish objects from measurements of their pulse backscatter signals is a topic of considerable *** nondestructive detection,it encounter difficulty in identifying small pieces of defect,these targets hard to recognize because targets signal have to compete with other clutter *** to improve the performance of image for applying multifractal geometry,we must first gain a understanding of the characteristics of image clutters.

关键词： ultrasonic image defective target return multifractal

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Despeckling Algorithm on ultrasonic image Using Adaptive Block-Based Singular Value Decomposition

Despeckling Algorithm on Ultrasonic Image Using Adaptive Blo...

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2007亚洲光电子会议电子成像与多媒体技术分会场

作者： Napa Sae-Bae Somkait Udomhunsakul King Mongkut’s Institute of Technology Ladkrabang Faculty of Engineering Information Engineering Department Bangkok Thailand

Speckle noise reduction is an important technique to enhance the quality of ultrasonic image. In this paper, a despeckling algorithm based on an adaptive block-based singular value decomposition filtering (BSVD) applied on ultrasonic images is presented. Instead of applying BSVD directly to ultrasonic image, we propose to apply BSVD on the noisy edge image version obtained from the difference between the logarithmic transformations of the original image and blur image version of its. The recovered image is performed by combining the speckle noise-free edge image with blur image version of its. Finally, exponential transformation is applied in order to get the reconstructed image. To evaluate our algorithm compared with well-know algorithms such as Lee filter, Kuan filter, Homomorphic Wiener filter, median filter and wavelet soft thresholding, four image quality measurements, which are Mean Square Error (MSE), Signal to MSE (S/MSE), Edge preservation ( ), and Correlation measurement ( ), are used. From the results, it clearly shows that the proposed algorithm outperforms other methods in terms of quantitative and subjective assessments.

关键词： ultrasonic image SVD Despeckling singular value thresholding speckle noise speckle denoising

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Analysis and Management System of Digital ultrasonic image

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Chinese Journal of Biomedical Engineering(English Edition) 2008年第3期17卷 130-133页

作者： TAO Qiang ZHANG Hai-yan LI Xia WANG Ke Biomedical Engineering Institute of Capital Medical University Beijing 100069 China

This paper presents the analysis and management system of digital ultrasonic image. The system can manage medical ultrasonic image by collecting, saving and transferring, and realize that section offices of ultrasonic image in hospital network manage. The system use network technology in transferring image between ultrasonic equipments to share patient data in ultrasonic equipments. And doctors can input patient diagnostic report,saved by text file and case history, digitally managed. The system can be realized by Visual C++ which make windows applied. The system can be brought forward because PACS prevail with various hospitals,but PACS is expensive. In view of this status, we put forward to the analysis and management system of digital ultrasonic image,which is similar to PACS.

关键词： ultrasonic image local area network PACS

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维普期刊数据库

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Internal Defects Detection Method of the Railway Track Based on Generalization Features Cluster Under ultrasonic images

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Chinese Journal of Mechanical Engineering 2022年第5期35卷 364-381页

作者： Fupei Wu Xiaoyang Xie Jiahua Guo Qinghua Li Key Laboratory of Intelligent Manufacturing Technology Ministry of EducationShantou UniversityShantou 515063China

There may be several internal defects in railway track work that have different shapes and distribution rules,and these defects affect the safety of high-speed *** reliable detection models and methods for these internal defects remains a challenging *** address this challenge,in this study,an intelligent detection method based on a generalization feature cluster is proposed for internal defects of railway ***,the defects are classified and counted according to their shape and location ***,generalized features of the internal defects are extracted and formulated based on the maximum difference between different types of defects and the maximum tolerance among same defects’***,the extracted generalized features are expressed by function constraints,and formulated as generalization feature clusters to classify and identify internal defects in the railway ***,to improve the detection reliability and speed,a reduced-dimension method of the generalization feature clusters is presented in this *** on this reduced-dimension feature and strongly constrained generalized features,the K-means clustering algorithm is developed for defect clustering,and good clustering results are *** the defects in the rail head region,the clustering accuracy is over 95%,and the Davies-Bouldin index(DBI)index is negligible,which indicates the validation of the proposed generalization features with strong *** results prove that the accuracy of the proposed method based on generalization feature clusters is up to 97.55%,and the average detection time is 0.12 s/frame,which indicates that it performs well in adaptability,high accuracy,and detection speed under complex working *** proposed algorithm can effectively detect internal defects in railway tracks using an established generalization feature cluster model.

关键词： Railway track Generalization features cluster Defects classification ultrasonic image Defects detection

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