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a Novel Fuzzy Clustering Method Based on Chaos Immune Evolutionary Algorithm for Edge Detection in ImageProcessing

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 1,   Pages 85-89 doi: 10.1007/s11465-005-0023-6

Abstract: chaos immune evolutionary algorithm (CIEFCM) is presented to solve fuzzy edge detection problems in imageprocessing.

Keywords： disturbance amplitude     disturbance     diversity     generation     processing    

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Affective rating ranking based on face images in arousal-valence dimensional space None

Guo-peng XU, Hai-tang LU, Fei-fei ZHANG, Qi-rong MAO

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 6,   Pages 783-795 doi: 10.1631/FITEE.1700270

Abstract: In dimensional affect recognition, the machine learning methods, which are used to model and predict affect, are mostly classification and regression. However, the annotation in the dimensional affect space usually takes the form of a continuous real value which has an ordinal property. The aforementioned methods do not focus on taking advantage of this important information. Therefore, we propose an affective rating ranking framework for affect recognition based on face images in the valence and arousal dimensional space. Our approach can appropriately use the ordinal information among affective ratings which are generated by discretizing continuous annotations. Specifically, we first train a series of basic cost-sensitive binary classifiers, each of which uses all samples relabeled according to the comparison results between corresponding ratings and a given rank of a binary classifier. We obtain the final affective ratings by aggregating the outputs of binary classifiers. By comparing the experimental results with the baseline and deep learning based classification and regression methods on the benchmarking database of the AVEC 2015 Challenge and the selected subset of SEMAINE database, we find that our ordinal ranking method is effective in both arousal and valence dimensions.

Keywords： Ordinal ranking     Dimensional affect recognition     Valence     Arousal     Facial image processing    

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Three-dimensional reconstruction of light microscopy image sections: present and future

Yuzhen Wang,Rui Xu,Gaoxing Luo,Jun Wu

Frontiers of Medicine 2015, Volume 9, Issue 1,   Pages 30-45 doi: 10.1007/s11684-014-0337-z

Abstract:

Three-dimensional (3D) image reconstruction technologies can reveal previously hidden microstructures

Keywords： microtomy     3D imaging     computer-assisted image processing     3D printing     tissue scaffold    

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Dynamic modeling and damage analysis of debris cloud fragments produced by hypervelocity impacts via imageprocessing Research Article

Ru ZENG, Yan SONG, Weizhen LV,zengru_neo@163.com,sonya@usst.edu.cn,hala_lwz@163.com

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 4,   Pages 555-570 doi: 10.1631/FITEE.2100049

Abstract: Based on the extracted information, image matching of debris is conducted and the trajectory of is modeled

Keywords： Debris clouds     Hypervelocity impact     Image processing     Damage estimation    

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UsingKinect for real-time emotion recognition via facial expressions

Qi-rong MAO,Xin-yu PAN,Yong-zhao ZHAN,Xiang-jun SHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 4,   Pages 272-282 doi: 10.1631/FITEE.1400209

Abstract: Emotion recognition via facial expressions (ERFE) has attracted a great deal of interest with recentIn this paper, we propose a real-time emotion recognition approach based on both 2D and 3D facial expressionTo capture the deformation of the 3D mesh during facial expression, we combine the features of animationemotional profiles (IEPs) and maximum confidence is proposed to recognize emotions with these real-time facial

Keywords： Kinect     Emotion recognition     Facial expression     Real-time classification     Fusion algorithm     Support vector    

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Automatic image enhancement by learning adaptive patch selection None

Na LI, Jian ZHAN

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 2,   Pages 206-221 doi: 10.1631/FITEE.1700125

Abstract: Many existing image enhancement algorithms are patch based and the patch size is always fixed throughoutthe image.In this study, we propose an automatic image enhancement method based on adaptive patch selection usingExperimental results demonstrate that our method can provide a significant improvement in existing patch-based image

Keywords： Image enhancement     Contrast enhancement     Dark channel     Bright channel     Adaptive patch based processing    

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Research of Lossless Image Compression Base on Level-scalability

Li Luwei,Zhou Shuoyan,Cai Yiyu

Strategic Study of CAE 2005, Volume 7, Issue 10,   Pages 33-37

Abstract:

A level-embedded lossless image compression method for continuous-tone still images is presented.Level (bit-plane) scalability is achieved by separating the image into two layers (the base layer andA comparison of the proposed scheme with a number of scalable and non-scalable lossless image compression

Keywords： data processing techniques     lossless image compression     context-based model     embedded level    

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Image analysis of soil failure on defective underground pipe due to cyclic water supply and drainage

Toshifumi MUKUNOKI, Naoko KUMANO, Jun OTANI

Frontiers of Structural and Civil Engineering 2012, Volume 6, Issue 2,   Pages 85-100 doi: 10.1007/s11709-012-0159-5

Abstract: The ground subsidence on the underground pipe often is caused with the reduction of the effective stress and the loss of suction in the base course and then, soil drainage into the pipe. The final formation of the cavity growth in the ground was observed as the ground subsidence. Authors focused this problem and hence performed model tests with water-inflow and drainage cycle in the model ground. The mechanism of cavity generation in the model ground was observed using an X-ray Computed Tomography (CT) scanner. In those studies, water was supplied into the model grounds from the defected underground pipe model in case of the change of relative density and grain size distribution. As results, it was observed that the loosening area was generated from the defected part with water-inflow and some of the soil particles in the ground were drained into the underground pipe through the defected part. And afterward, the cavity was generated just above the defected part of the model pipe in the ground. Based on this observation, it might be said that the bulk density of soil around the defected pipe played one of key factor to generate the cavity in the ground. Moreover, the dimension of the defected part should be related to the magnification of the ground subsidence, in particular, crack width on a sewerage pipe and particle size would be the quantitative factor to evaluate the magnification of the ground subsidence. ?In this paper, it was concluded that the low relative density of soil would become the critical factor to cause the fatal failure of model ground if the maximum grain size was close to the dimension of crack width of defective part. The fatal collapse of the ground with high relative density more than 80% would be avoided in a few cycles of water inflow and soil drainage.

Keywords： relative density     grain property     model test     road subsidence     underground pipe     image processing     X-ray CT    

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Feature extraction of hyperspectral images for detecting immature green citrus fruit

Yongjun DING, Won Suk LEE, Minzan LI

Frontiers of Agricultural Science and Engineering 2018, Volume 5, Issue 4,   Pages 475-484 doi: 10.15302/J-FASE-2018241

Abstract: wavebands and to construct multispectral images from the original hyperspectral images for further processingThen, histogram threshold segmentation using NDVI of 804 and 677 nm was implemented to remove image

Keywords： hyperspectral     green citrus     image processing     fruit detection     precision agriculture     yield mapping    

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Synchronous observation of rising soluble bubble through quiescent solution

Yifu ZHANG , Shuai TIAN , Weizhong LI , Yongchen SONG ,

Frontiers in Energy 2009, Volume 3, Issue 3,   Pages 307-312 doi: 10.1007/s11708-009-0028-7

Abstract: An experimental method using computer image processing technology (CIPT) was proposed to observe and

Keywords： soluble bubble     mass transfer     synchronous observation     computer image processing    

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Chitosan/polyethylene glycol impregnated activated carbons: Synthesis, characterization and adsorption performance

Ehsan Salehi, Fereshteh Soroush, Maryam Momeni, Aboulfazl Barati, Ali Khakpour

Frontiers of Chemical Science and Engineering 2017, Volume 11, Issue 4,   Pages 575-585 doi: 10.1007/s11705-017-1650-2

Abstract: Novel modified activated carbons (ACs) with enhanced adsorptive properties were obtained coating by chitosan (CS), polyethylene glycol (PEG) and blends of the two polymers (0:1, 1:0, 1:1, 1:2 and 2:1 wt/wt) on ACs by an impregnation technique. The adsorption performances of the pristine, acidified and polymer-impregnated ACs were studied using methylene blue as a model adsorbate. The adsorbents were characterized using Fourier transform infrared spectroscopy, scanning electron microscopy and abrasion hardness tests. The average coating thicknesses were between 10 to 23 microns. The pore sizes, pore densities and pore capacities of the activated carbons increased as the wt-% PEG in the coating increased. The highest adsorption capacity (424.7 mg/g) was obtained for the chitosan-coated ACs and this adsorption was well described by the Langmuir isotherm model. The kinetic results were best described by the pseudo-second-order kinetic model. The highest rate constant was obtained with the ACs modified with the CS:PEG (2:1) coating and this result was almost 2.6 times greater than that of the unmodified ACs. The CS/PEG impregnated ACs also displayed superior hardness (~90%), compared to unmodified ACs (~85%). Overall the chitosan had a greater effect on improving adsorption capacity whereas the polyethylene glycol enhanced the adsorption rate.

Keywords： carbon biocomposites     impregnation     chitosan     polyethylene glycol     image processing    

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The State-of-the-Art Review on Applications of Intrusive Sensing, Image Processing Techniques, and Machine Review

Yue Hou, Qiuhan Li, Chen Zhang, Guoyang Lu, Zhoujing Ye, Yihan Chen, Linbing Wang, Dandan Cao

Engineering 2021, Volume 7, Issue 6,   Pages 845-856 doi: 10.1016/j.eng.2020.07.030

Abstract: employed for the collection and analysis of such data, including various intrusive sensing techniques, imageprocessing techniques, and machine learning methods.

Keywords： Pavement monitoring and analysis     The state-of-the-art review     Intrusive sensing     Image processing techniques    

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A study on fatigue damage of asphalt mixture under different compaction using 3D-microstructural characteristics

Jing HU, Pengfei LIU, Bernhard STEINAUER

Frontiers of Structural and Civil Engineering 2017, Volume 11, Issue 3,   Pages 329-337 doi: 10.1007/s11709-017-0407-9

Abstract: The aggregate particles and air-voids were extracted using Digital Image Processing (DIP), so the relationship

Keywords： asphalt mixture     microstructure     morphology     digital image processing     fatigue damage    

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Subspace transform induced robust similarity measure for facial images

Jian Zhang, Heng Zhang, Li-ling Bo, Hong-ran Li, Shuai Xu, Dong-qing Yuan,zhangjian@jou.edu.cn,zhangheng@jou.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 9,   Pages 1267-1412 doi: 10.1631/FITEE.1900552

Abstract: Specifically, the TSM method robustly determines the similarity between two well-aligned frontal facial
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Automatic Visual Leakage Detection and Localization from Pipelines in Chemical Process Plants Using Machine Vision Techniques Reiew

Mina Fahimipirehgalin, Emanuel Trunzer, Matthias Odenweller, Birgit Vogel-Heuser

Engineering 2021, Volume 7, Issue 6,   Pages 758-776 doi: 10.1016/j.eng.2020.08.026

Abstract:

Liquid leakage from pipelines is a critical issue in large-scale process plants. Damage in pipelines affects the normal operation of the plant and increases maintenance costs. Furthermore, it causes unsafe and hazardous situations for operators. Therefore, the detection and localization of leakages is a crucial task for maintenance and condition monitoring. Recently, the use of infrared (IR) cameras was found to be a promising approach for leakage detection in large-scale plants. IR cameras can capture leaking liquid if it has a higher (or lower) temperature than its surroundings. In this paper, a method based on IR video data and machine vision techniques is proposed to detect and localize liquid leakages in a chemical process plant. Since the proposed method is a vision-based method and does not consider the physical properties of the leaking liquid, it is applicable for any type of liquid leakage (i.e., water, oil, etc.). In this method, subsequent frames are subtracted and divided into blocks. Then, principle component analysis is performed in each block to extract features from the blocks. All subtracted frames within the blocks are individually transferred to feature vectors, which are used as a basis for classifying the blocks. The k-nearest neighbor algorithm is used to classify the blocks as normal (without leakage) or anomalous (with leakage). Finally, the positions of the leakages are determined in each anomalous block. In order to evaluate the approach, two datasets with two different formats, consisting of video footage of a laboratory demonstrator plant captured by an IR camera, are considered. The results show that the proposed method is a promising approach to detect and localize leakages from pipelines using IR videos. The proposed method has high accuracy and a reasonable detection time for leakage detection. The possibility of extending the proposed method to a real industrial plant and the limitations of this method are discussed at the end.

Keywords： Leakage detection and localization     Image analysis     Image pre-processing     Principle component analysis    

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Title Author Date Type Operation

a Novel Fuzzy Clustering Method Based on Chaos Immune Evolutionary Algorithm for Edge Detection in ImageProcessing

Journal Article

Affective rating ranking based on face images in arousal-valence dimensional space

Guo-peng XU, Hai-tang LU, Fei-fei ZHANG, Qi-rong MAO

Journal Article

Three-dimensional reconstruction of light microscopy image sections: present and future

Yuzhen Wang,Rui Xu,Gaoxing Luo,Jun Wu

Journal Article

Dynamic modeling and damage analysis of debris cloud fragments produced by hypervelocity impacts via imageprocessing

Ru ZENG, Yan SONG, Weizhen LV,zengru_neo@163.com,sonya@usst.edu.cn,hala_lwz@163.com

Journal Article

UsingKinect for real-time emotion recognition via facial expressions

Qi-rong MAO,Xin-yu PAN,Yong-zhao ZHAN,Xiang-jun SHEN

Journal Article

Automatic image enhancement by learning adaptive patch selection

Na LI, Jian ZHAN

Journal Article

Research of Lossless Image Compression Base on Level-scalability

Li Luwei,Zhou Shuoyan,Cai Yiyu

Journal Article

Image analysis of soil failure on defective underground pipe due to cyclic water supply and drainage

Toshifumi MUKUNOKI, Naoko KUMANO, Jun OTANI

Journal Article

Feature extraction of hyperspectral images for detecting immature green citrus fruit

Yongjun DING, Won Suk LEE, Minzan LI

Journal Article

Synchronous observation of rising soluble bubble through quiescent solution

Yifu ZHANG , Shuai TIAN , Weizhong LI , Yongchen SONG ,

Journal Article

Chitosan/polyethylene glycol impregnated activated carbons: Synthesis, characterization and adsorption performance

Ehsan Salehi, Fereshteh Soroush, Maryam Momeni, Aboulfazl Barati, Ali Khakpour

Journal Article

The State-of-the-Art Review on Applications of Intrusive Sensing, Image Processing Techniques, and Machine

Yue Hou, Qiuhan Li, Chen Zhang, Guoyang Lu, Zhoujing Ye, Yihan Chen, Linbing Wang, Dandan Cao

Journal Article

A study on fatigue damage of asphalt mixture under different compaction using 3D-microstructural characteristics

Jing HU, Pengfei LIU, Bernhard STEINAUER

Journal Article

Subspace transform induced robust similarity measure for facial images

Jian Zhang, Heng Zhang, Li-ling Bo, Hong-ran Li, Shuai Xu, Dong-qing Yuan,zhangjian@jou.edu.cn,zhangheng@jou.edu.cn

Journal Article

Automatic Visual Leakage Detection and Localization from Pipelines in Chemical Process Plants Using Machine Vision Techniques

Mina Fahimipirehgalin, Emanuel Trunzer, Matthias Odenweller, Birgit Vogel-Heuser

Journal Article