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algorithm based on the finite ridgelet transform for enhancing faint pavement cracks

OPTICAL ENGINEERING 2008年第1期47卷 017004-1-017004-1页

作者： Wang, Gang Xu, Xiu-Wei Xiao, Liang He, An-zhi Ludong Univ Sch Phys & Elect Engn Yantai Shandong Peoples R China Nanjing Univ Sci & Technol Sch Sci Nanjing 210094 Jiangsu Peoples R China

A novel image enhancement algorithm for faint pavement cracks is proposed, based on the finite ridgelet transform (FRIT). In high-resolution FRIT subbands, typical linear singularities of the image are represented by a few coefficients, while randomly located noisy singularities are unlikely to produce significant coefficients. The parameters of an enhancement function can be determined through analyzing the distribution of the high-resolution FRIT coefficients. Therefore, a scheme based on modifying FRIT coefficients should be very effective in enhancing the linear singularities and suppressing the noise. In general, an entire pavement crack is a curve. A smooth partition method is proposed to divide a pavement crack image into local windows where the crack looks straight. Then the FRIT-based enhancement method can be applied to each piece of the whole crack. Experiments verify that faint crack signals submerged in the complicated background can be displayed efficiently by this algorithm. (C) 2008 Society of Photo-Optical Instrumentation Engineers.

关键词： finite ridgelet transform (FRIT) Radon transform enhancement algorithm smooth partition faint pavement cracks

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Research on X-ray image processing technology for laser welded joints of aluminum alloy

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2018年第1-4期99卷 683-694页

作者： Zhan, Xiaohong Zhang, Dan Yu, Haisong Chen, Jie Li, Hao Wei, Yanhong Nanjing Univ Aeronaut & Astronaut Coll Mat Sci & Technol Nanjing 210016 Jiangsu Peoples R China Shanghai Aircraft Mfg Co Ltd Inst Aeronaut Mfg Technol Shanghai 200436 Peoples R China

Weldment X-ray image processing has great significance on the subsequent segmentation and extraction of weld seam and defects. In the current study, X-ray image for laser welding of aluminum alloy was adopted as experimental object. A new image denoising algorithm was proposed, which was combined with weighted adaptive median filter and noise-reduction algorithm based on wavelet transform. An improved adaptive fuzzy enhancement algorithm was put forward, which was based on traditional Pal-King fuzzy enhancement algorithm. Different noise-reduction algorithms were performed to denoise the X-ray image. Comprehensive evaluation of noise-reduction effect was conducted by comparing the processing effect, 3D grayscale distribution, and image quality evaluation index after different denoising algorithms. Moreover, fuzzy entropy and fuzzy index were used to estimate the enhancement effect of traditional Pal-King fuzzy enhancement algorithm and improved adaptive fuzzy enhancement algorithm. The results revealed that the noise-reduction effect and the image quality obtained by proposed algorithm were better than separately using weighted adaptive median filter or noise-reduction algorithm based on wavelet transform. Furthermore, after processing with improved adaptive fuzzy enhancement algorithm, the image detail information was more prominent, and sense of hierarchy was stronger.

关键词： X-ray NDT Image processing Noise-reduction algorithm enhancement algorithm

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CT brain image advancement for ICH diagnosis

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HEALTHCARE TECHNOLOGY LETTERS 2020年第1期7卷 1-6页

作者： Amir, Nor Shahirah Kang, Law Zhe Mukari, Shahizon Azura Sahathevan, Ramesh Chellappan, Kalaivani Univ Kebangsaan Malaysia Fac Engn & Built Environm Dept Elect Elect & Syst Ukm Bangi 43600 Selangor Malaysia Univ Kebangsaan Malaysia Dept Neurol & Radiol Med Ctr Jalan Yaacob Latif Kuala Lumpur 56000 Malaysia Ballarat Base Hosp Dept Internal Med Serv Ballarat Hlth Serv Ballarat Vic Australia Univ Melbourne Fac Med Dent & Hlth Sci Melbourne Vic Australia Florey Inst Neurosci & Mental Hlth Melbourne Vic Australia

A critical step in detection of primary intracerebral haemorrhage (ICH) is an accurate assessment of computed tomography (CT) brain images. The correct diagnosis relies on imaging modality and quality of acquired images. The authors present an enhancement algorithm which can improve the clarity of edges on CT images. About 40 samples of CT brain images with final diagnosis of primary ICH were obtained from the UKM Medical Centre in Digital Imaging and Communication in Medicine format. The images resized from 512 x 512 to 256 x 256 pixel resolution to reduce processing time. This Letter comprises of two main sections;the first is denoising using Wiener filter, non-local means and wavelet;the second section focuses on image enhancement using a modified unsharp masking (UM) algorithm to improve the visualisation of ICH. The combined approach of Wiener filter and modified UM algorithm outperforms other combinations with average values of mean square error, peak signal-to-noise ratio, variance and structural similarity index of 2.89, 31.72, 0.12 and 0.98, respectively. The reliability of proposed algorithm was evaluated by three blinded assessors which achieved a median score of 65%. This approach provides reliable validation for the proposed algorithm which has potential in improving image analysis.

关键词： image denoising image segmentation Wiener filters computerised tomography brain medical image processing image enhancement CT brain image advancement ICH diagnosis primary intracerebral haemorrhage computed tomography brain images correct diagnosis imaging modality enhancement algorithm CT images CT brain images final diagnosis primary ICH UKM Medical Centre Digital Imaging main sections Wiener filter wavelet image enhancement modified unsharp masking algorithm UM algorithm image analysis

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Novel Approach to Enhance the Performance of Production Systems Using Lean Tools

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JORDAN JOURNAL OF MECHANICAL AND INDUSTRIAL ENGINEERING 2016年第3期10卷 215-229页

作者： Kaylani, Hazem Almuhtady, Ahmad Atieh, Anas M. German Jordanian Univ Dept Ind Engn Sch Appl Tech Sci Amman Madaba St Amman Jordan German Jordanian Univ Mech & Maintenance Engn Dept Sch Appl Tech Sci Amman Madaba St Amman Jordan

Value Stream Mapping (VSM) is a tool used for analyzing the current state of a production system and designing a future state by analyzing and improving the flow of material and reducing inefficiencies. However, aiming at improving performance without considering potential machine failures and other uncertainties in the production process may lead to an inaccurate future value stream map. The purpose of the present study is to introduce a novel approach that combines discrete event simulation, Design Of Experiments (DOE), and Failure Modes and Effects Analysis (FMEA) to enhance the VSM processes. Simulation modeling is utilized to evaluate production system performance and the severity of potential failure modes under several operational conditions. FMEA and DOE are then used to select the best systems enhancements which can be used to generate future map. The results of our approach show that failure modes can drastically affect the system performance if not taken into consideration, resulting in a non-representative future VSM. The proper selection of operational levels can reduce the severity of failures and at the same can provide high performance levels. (C) 2016 Jordan Journal of Mechanical and Industrial Engineering. All rights reserved

关键词： Value Stream Mapping (VSM) simulation Design Of Experiments (DOE) Failure Mode and Effect Analysis (FMEA) process flowchart enhancement algorithm glass fabrication case study

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Adjustment of Visual Information for Visually Impaired People 58

Adjustment of Visual Information for Visually Impaired Peopl...

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58th ELMAR International Symposium

作者： Filo, Nikola Mandic, Lidija Poljicak, Ante Univ Zagreb Fac Graph Arts Getaldiceva 2 Zagreb 41000 Croatia

ISBN: (纸本)9789531842211

The aim of this work is to test algorithms for image enhancement with different values in the algorithm and to test those algorithms on the different accelerators that could be used for medical aids. The results of this research show advantages and disadvantages of equipment that we used and also can indicate implantation of algorithm into portable devices. Five selected images were filtered through proposed algorithm and compared with golden standard through metrics MSE, PSNR and SSIM. Speeup for edge detector was tested on different machines.

关键词： Low Vision Retina enhancement algorithm Hardware Implementation

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A Review on Detection and Recognition of Text

A Review on Detection and Recognition of Text

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IEEE International Conference on Innovations in Power and Advanced Computing Technologies

作者： Maske, Minakshi Thakare, Shubhada Govt Coll Engn Amravati Dept Elect Engn Amravati India

ISBN: (纸本)9781538681909

With dust weather becomes more common, dusty images is increasing. The text regions in dusty images always exist some problems like blur, text features weakened or lost, low definition, low contrast which greatly affects to understanding the information from images. Text in images can have significant importance and useful information and hence the text recognition in images has becomes one of the important topic of intelligent information processing. There is a weakening of text feature in dusty image hence traditional algorithm can not be apply for text recognition in dusty images. To recognize the text from dusty image more efficient, introduce new method which has two modules. First, the dusty image is enhanced by enhancement algorithm and then text are detected and recognized in the enhanced image. This paper presents literature review of work on scene images text recognition in past few years. Their corresponding advantages and disadvantages and overviews on various text related application are also present.

关键词： dusty images enhancement algorithm detection and recognition of text

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Text Detection for Dust Image Based on Deep Learning 33

Text Detection for Dust Image Based on Deep Learning

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33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Liu, Hao Li, Ce Jia, Shengze Zhang, Dong Lanzhou Univ Technol Coll Elect & Informat Engn Lanzhou Gansu Peoples R China

ISBN: (纸本)9781538672556

With a large number of images, we rely on the text in images to understand the image quickly and extract useful information. So text detection in images has become one of the important topics of intelligent information processing. With the deteriorating environment, dust weather is more and more common, and text regions in dust images always exit some questions that blur, text features weakened or lost greatly affects our understanding of images and also limits extracting text information from images. Therefore, the traditional algorithm is not good at text detection of dust images. In order to solve these problems, a new method is proposed to detect the dust image text, which is divided into two modules. Firstly, the dust image is enhanced by the dust image enhancement algorithm based on color transfer, and the text and non-text regions in the image are divided by the maximally stable extremal regions, which greatly reduces the computational cost. Next, we choose the text candidate region through convolutional neural network. And then text lines are obtained by the run length smoothing algorithm. Finally, the non-text regions are removed by gaussian smoothing and candidate area filtering to realize text detection in dust images. The experimental results show that the algorithm can be used to detect text regions in dust images with good performance.

关键词： dust image enhancement algorithm text detection

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Optimization of Apriori algorithm Based on Binary Coding and Matrix Processing 7

Optimization of Apriori Algorithm Based on Binary Coding and...

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7th IEEE International Conference on Information Systems and Computer Aided Education, ICISCAE 2024

作者： Han, Xinxin Wang, Jiao Xiong, Xueguan Wang, Liuling Yang, Xi Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9798350350760

—This research delves into the classic Apriori algorithm, comprehensively analyzing its concepts, properties, and existing limitations, and provides a detailed demonstration of the algorithm's execution flow through a case study. Aiming at the problems of traditional Apriori algorithms, such as low execution efficiency, heavy I/O, and excessive computation, an enhancement algorithm is proposed: By binary coding, the transaction sets of different items and adopting the storage structure of matrix processing data, Logical AND operations are used to enhance the execution efficiency of the algorithm, it is essential to minimize the number of database scans required during the process of identifying frequent item sets. This practical and efficient optimization algorithm offers hope for improved data mining processes. ©2024 IEEE.

关键词： Apriori algorithm Correlation rules enhancement algorithm

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Methods of Improving Japanese-Chinese Machine Translation System through Machine Learning and Human-Computer Interaction

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ACM Transactions on Asian and Low-Resource Language Information Processing 1000年

作者： Yuwei Ma Yu Qian College of Foreign Languages Changchun University of Finance and Economics Changchun 130122 Jilin China Changchun University of Finance and Economics Changchun 130122 Jilin China

With globalization, the exchange of people between different countries is becoming more frequent. Due to different languages, there are serious obstacles to personnel exchanges. To a large extent, they hinder the growth of industries such as economy, culture and tourism in each country. The emergence of Machine Translation (MT) has effectively improved the problem of language barriers, and greatly reduced the workload of translators in text translation. However, MT does not have the same flexible flexibility as human translation. It just translates the text word by word, which is often difficult to meet people's higher needs. This paper proposed to build a Japanese-Chinese MT system and integrate machine learning and Human-Computer Interaction (HCI) technology into the system. To further enhance the efficiency of the system, enhancement algorithms were also applied to the system to optimize the performance of the system. From the experimental results, in terms of BLEU (Bilingual Evaluation Understudy) index, the average BLEU index of the algorithm in this paper was 8.59, and that of the traditional algorithm was 6.55. In terms of translation precision, the average precision of the algorithm in this paper was 91.53%, while that of the traditional algorithm was 87.28%. In terms of translation readability, the average readability of the algorithm in this paper was 93.32%, while that of the traditional algorithm was 89.22%. By comparison, the average BLEU index of the algorithm in this paper has increased by 2.04; the average accuracy of translation increased by 4.25%; the average readability increased by 4.1%. From the above data, it was evident that the enhancement algorithm can optimize the performance of the Japanese-Chinese MT system well.

关键词： Machine Learning Human-Computer Interaction Machine Translation Japanese-Chinese Machine Translation System enhancement algorithm

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