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Flame interaction and flow characteristic analysis of hydrogen-rich micromix multi-nozzle array using simultaneous high-speed OH-PLIF/Chemiluminescence and PIV techniques

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2025年 128卷 208-220页

作者： Cao, Zhen Luo, Yuxin Yang, Chaobo Peng, Jiangbo Zhu, Tao Shao, Weiwei Yuan, Xun Chen, Dengke Xing, Chang Qiu, PengHua Yu, Xin Harbin Inst Technol Natl Key Lab Laser Spatial Informat Harbin 150001 Peoples R China Harbin Inst Technol Postdoctoral Res Stn Power Engn & Engn Thermophys Harbin 150001 Peoples R China Harbin Inst Technol Sch Energy Sci & Engn Harbin 150001 Peoples R China Chinese Acad Sci Inst Engn Thermophys Beijing 100190 Peoples R China

Micromixing combustion technology effectively prevents flashback by achieving highly premixed fuel and air suitable for a hydrogen-rich fuel. In this study, a mesoscale multi-nozzle array was constructed for burning H2/ CH4/air flames with high hydrogen content. The flame structures were characterized using simultaneous Planar Laser-Induced Fluorescence (PLIF) and OH* chemiluminescence imaging. Particle image velocimetry (PIV) was also used to investigate the flow-field structures. An improved watershed algorithm was developed to analyze the flame and flow characteristics. The results revealed that lower equivalence ratios concentrated the heat release and reduced the flow velocity. The outer flame, located far from the central igniter, demonstrated increased surface wrinkling and a higher velocity. The results indicated that the interactions between adjacent flames significantly influenced both the local and global flame behaviors. The flow and flame features revealed marked differences among the nozzles, providing deep insights into the characteristics of multi-nozzle hydrogen-rich combustion.

关键词： High-speed laser diagnostics Micro-mixing hydrogen combustion Multi-nozzle array Flow and flame features watershed algorithm

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Improved level set method for particle reconstruction from X-ray computed tomography images

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POWDER TECHNOLOGY 2025年 455卷

作者： Wang, Tingxuan Fei, Wenbin Ehinger, Krista A. Drummond, Tom W. Narsilio, Guillermo A. Hunan Univ Coll Civil Engn A316 Changsha 410082 Hunan Peoples R China Univ Melbourne Sch Comp & Informat Syst Parkville Australia Univ Melbourne Dept Infrastructure Engn Parkville Australia Minist Educ Key Lab Bldg Safety & Energy Efficiency Changsha 410082 Hunan Peoples R China

The heat and fluid flow properties of granular materials are largely controlled by their 3D microstructures. With recent advancements in image-based network modeling, heat transfer and fluid dynamic physics can be effectively simulated. Model accuracy depends on precise 3D reconstruction of particles from X-ray computed tomography (XRCT) images;however, existing workflows that combine watershed algorithms with level set methods require subjective manual inputs in preprocessing and lack controllability in optimization processes. To address these problems, this work proposes an automated workflow that can achieve high precision in the 3D reconstruction of particles. Oversegmentation instances by the traditional watershed algorithm are eliminated through morphological dilations, providing better inputs for the level set optimization process to lay a solid foundation for particle boundary extraction. The results of the proposed level set method are validated with paired multiresolution images of nearly spherical Ottawa and irregular angular sand. Compared with the current state-of-the-art method, the proposed method consistently and significantly obtains smoother particle boundaries and more accurate particle volumes and interparticle contact areas.

关键词： 3D segmentation Level set Particle reconstruction watershed algorithm Contact area estimation

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The extraction algorithm of color disease spot image based on Otsu and watershed

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SOFT COMPUTING 2020年第10期24卷 7253-7263页

作者： Xiong, Lu Zhang, Dongbo Li, Kangshun Zhang, Lixia Zhongkai Univ Agr & Engn Coll Automat Guangzhou 510225 Peoples R China Guangdong Inst Intelligent Mfg Guangzhou 510070 Peoples R China South China Agr Univ Coll Math & Informat Guangzhou 521000 Peoples R China

In this paper, an extraction algorithm of color disease spot image based on Otsu and watershed is proposed to overcome the problem of excessive segmentation in the traditional watershed algorithm. The proposed algorithm converts the color space of the color spot image to calculate the component gradient that is not interfered by the reflected light in the new color space. Then, final gradient image is obtained from the gradient image reconstructed by open and close operation under the different-sized structural elements. The label from the final gradient image is extracted by Otsu algorithm, and then, the H-minima transform is used to modify the labeled image. The modified gradient image is transformed with a label by the watershed algorithm. Finally, the extraction of the disease spot is implemented. The experimental results show that the proposed approach obtains accurate and continuous target contour and reaches the requirement of human visual characteristics. Compared with other similar algorithms, the proposed algorithm can effectively suppress the impact of reflected light, optimize the extraction results of disease spot, better maintain the information of disease spot image, and improve the robustness and the applicability.

关键词： watershed algorithm Otsu algorithm Color disease spot image H-minima transformation

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Quantum evolutionary clustering algorithm based on watershed applied to SAR image segmentation

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NEUROCOMPUTING 2012年 87卷 90-98页

作者： Li, Yangyang Shi, Hongzhu Jiao, Licheng Liu, Ruochen Xidian Univ Minist Educ China Key Lab Intelligent Percept & Image Understanding Xian 710071 Peoples R China

The goal of segmentation is to partition an image into disjoint regions. In this paper, the segmentation problem based on partition clustering is viewed as a combinatorial optimization problem. A new algorithm called a quantum evolutionary clustering algorithm based on watershed (QWC) is proposed. In the new algorithm, the original image is first partitioned into small pieces by watershed algorithm, and the quantum-inspired evolutionary algorithm is used to search the optimal clustering center, and finally obtain the segmentation result. Experimental results show that the proposed method is effective for texture image and SAR image segmentation, compared with QICW, the genetic clustering algorithm based on watershed (W-GAC) and K-means algorithm based on watershed (W-KM). (c) 2012 Elsevier B.V. All rights reserved.

关键词： Quantum evolutionary clustering algorithm watershed algorithm SAR image segmentation

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Cell Counting algorithm Using Radius Variation, watershed and Distance Transform

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JOURNAL OF INFORMATION PROCESSING SYSTEMS 2020年第1期16卷 113-119页

作者： Kim, Taehoon Kim, Donggeun Lee, Sangjoon ILOODA Co Ltd Suwon South Korea LIG Nex1 Co Ltd Pangyo North Korea

This study proposed the structure of the cluster's cell counting algorithm for cell analysis. The image required for cell count is taken under a microscope. At present, the cell counting algorithm is reported to have a problem of low accuracy of results due to uneven shape and size clusters. To solve these problems, the proposed algorithm has a feature of calculating the number of cells in a cluster by applying a radius change analysis to the existing distance conversion and watershed algorithm. Later, cell counting algorithms are expected to yield reliable results if applied to the required field.

关键词： Cell-Counting Distance Transform Radius Variation Analysis watershed algorithm

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Tongue-coating image segmentation based on combination of morphological gradient and watershed algorithms

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IMAGING SCIENCE JOURNAL 2011年第6期59卷 311-316页

作者： Zhang, L. Qin, J. Zeng, Y. J. Beijing Univ Technol Ctr Biomed Engn Beijing 100022 Peoples R China Guangdong Univ Technol Comp Fac Guangzhou 510006 Guangdong Peoples R China Sun Yat Sen Univ Affiliated Hosp 1 TCM Dept Guangzhou 510080 Guangdong Peoples R China

The segmentation of tongue-coating images is very important to computer-aided traditional Chinese medicine (TCM) clinic diagnosis system. By now, algorithms for this segmentation are in low-accuracy or high-complexity. Upon the edge-gradient feature of tongue-coating images, a new segmenting method is presented in this paper, which combines edge and region processing technologies. With the new method, the multi-scale morphological gradient images of the original images are taken firstly, and then watershed algorithm is used to segment them so that tongue-coating images are separated. The following experimental results show this method's effectiveness and efficiency.

关键词： watershed algorithm morphological gradient multi-scale

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An Improved Image Segmentation algorithm Based on The watershed Transform 7

An Improved Image Segmentation Algorithm Based on The Waters...

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IEEE 7th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)

作者： Cui, Xuemei Yang, Guowei Deng, Yan Wu, Shaolong Qingdao Univ Coll Automat Engn Qingdao 266071 Shandong Peoples R China Nanchang Hangkong Univ Coll Informat Engn Nanchang 330063 Peoples R China

ISBN: (纸本)9781479944194

The watershed transform has a good response to the weak edge, but it is unable to obtain meaningful segmentation results directly by using the watershed transform to the phenomenon of excessive segmentation in image segmentation. A new segmentation algorithm base on improved watershed algorithm is proposed in this paper. By the different marks on the foreground and background objects, we can obtain better effect of segmentation with the application of watershed algorithm. Through the study of the characteristics of gradient image and morphological open close function reconstruction operations in image processing, a new tag extraction method will be designed by the new algorithm, which is by using the method of opening and closing by reconstruction operators to obtain marks and by controlling the closed reconstruction of structural elements in order to interested in the gradient image area the size of the tag. Then, extracted tag using morphological minimum calibration technology forces as an original local minimum value of the gradient image, and shields the original all local minimum value in the gradient image. In the end, watershed which is modified by the gradient of the image will have a image segmentation, in such aspects as outline eliminate over-segmentation and regional positioning have a very good segmentation effect.

关键词： image segmentation mathematical morphology watershed algorithm marker extraction

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An Efficient Implementation of Fuzzy C-Means and watershed algorithms for MRI Segmentation 8

An Efficient Implementation of Fuzzy C-Means and Watershed A...

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8th International Symposium on Telecommunications (IST)

作者： Hoseini, Farnaz Shahbahrami, Asadollah Islamic Azad Univ Rasht Branch Fac Engn Rasht Iran Univ Guilan Fac Engn Dept Comp Engn Rasht Iran

ISBN: (纸本)9781509034352

Image segmentation is one of the most common steps in digital image processing. It classifies a digital image into different segments. There are many algorithms for image segmentation such as thresholding, edge detection, and region growing, which finding a suitable algorithm for medical image segmentation is a challenging task. This is due to noise, low contrast, and steep light variations of medical images. The main goal of this paper is improving the performance of fuzzy c-means clustering. Improving is achieved using parallel implementation of this algorithm. Fuzzy c-means clustering is an important iterative clustering algorithm, but it is computationally intensive and it uses the same data between the iterations. The center of the clusters changes in each iteration, which requires considerable amount of time for large data sets. The parallel fuzzy c-means clustering is implemented by using task pipeline concept in CUDA technology. The experimental results show that the performance is improved up to 23.35x. After that watershed algorithm is applied for the final segmentation. The implementation results show that the accuracy of diagnosis in magnetic resonance imaging 97/33% is improved. This improvement is achieved using enhancing edges and reducing noises in images.

关键词： Parallel Fuzzy C-Means Clustering watershed algorithm Parallel Computing CUDA GPU

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Wavelet-based watershed for image segmentation algorithm

Wavelet-based watershed for image segmentation algorithm

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6th World Congress on Intelligent Control and Automation

作者： Chai, Yu-hua Gao, Li-qun Lu, Shun Tian, Lei Northeastern Univ Inst Informat Sci & Engn Shenyang 110004 Liaoning Prov Peoples R China Semicond Mfg Int Corp Beijing 100176 Peoples R China

ISBN: (纸本)1424403316

A watershed image segmentation method based on wavelet transform is proposed. Firstly, source image was filtered by multi-scale morphological filtering and the filtered image was decomposed by wavelet, then the low-frequency approximate image was segmented into many small regions by watershed algorithm and these regions were merged according to some region mergence rules to get the original segmentation image. Finally, the original segmentation image was projected into a full-resolution image by inverse-wavelet transform to get the final segmentation image. Utilizing multi-scale morphological filtering and the multi-resolution characteristic of wavelet transform, this method solves effectively the problems of sensitizing to noises and over-segmentation phenomenon of watershed algorithm, and the computing speed is improved.

关键词： wavelet transform image segmentation watershed algorithm morphological gradient reconstruction

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watershed Image Segmentation algorithm Base on Particle Swarm and Region Growing

Watershed Image Segmentation Algorithm Base on Particle Swar...

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International Conference on Intelligent Computing and Internet of Things

作者： Sun Hui-jie Harbin Normal Univ Coll Comp Sci & Informat Engn Harbin 150025 Heilongjiang Peoples R China

ISBN: (纸本)9781479975341

An improved watershed image segmentation algorithm is proposed to solve the problems of noise-sensitivity and over-segmentation. The new algorithm which combined region growing with classical watershed algorithm is established by constructing an objective function, the parameter of region growing is ensured based on Shannon entropy. The particle swarm optimization algorithm is employed to search global optimization of the objective function. Experimental results show that the new watershed image segmentation algorithm can solve effectively the problem of over-segmentation and turns out to be an efficient, accurate and applied image segmentation algorithm.

关键词： particle swarm optimization image segmentation region growing mathematical morphology watershed algorithm

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