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IEEE International Geoscience & Remote Sensing Symposium

作者： Du, Jianhao Chen, Yan Tong, Ling Li, Guang Guo, Caizheng Univ Elect Sci & Technol China Sch Automat Engn Chengdu 611731 Sichuan Peoples R China

ISBN: (纸本)9781509049516

Vegetation coverage is an important indicator for forecasting geological disasters in mountainous areas such as landslide. However, it is a challenge to extract vegetation coverage in complex terrain from SAR image. A major problem is that the variation of the backscatter coefficient of the same object varies with the local incidence angle. As a result, a large number of discrete points appear in the classification results. Focus on this problem, a region-based method of vegetation coverage monitoring has been presented in this paper. Based on the results of yamaguchi decomposition and SVM algorithm, the watershed algorithm is used to over-segment the image and regions are merged on a pixel-voting basis. When the modified method was applied on RADARSAT-2 data, the research results show that the completeness and correctness are improved compared with the method based on yamaguchi decomposition and svm algorithm.

关键词： SAR vegetation coverage region-based yamaguchi decomposition watershed algorithm

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Automatic Detection at Material Parasite Based on Microscopic Image Analysis

Automatic Detection at Material Parasite Based on Microscopi...

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作者： Bekele, Abebe Addis Ababa University

学位级别：硕士

Malaria is a serious global health problem and its diagnosis is usually done manually by compound light microscopy which is time consuming, tiresome and subjective. To support this manual method, in this master thesis, we designed and developed a system which is able to automatically detect plasmodium parasites from images of blood smears acquired by ourselves using a digital light microscope. In this method, blood smears taken from patients who were infected with plasmodium parasites were prepared. Digital images were then acquired by the light microscope and saved in the computer. Red blood cells (RBCs) are first segmented by marker control watershed algorithm, where the foreground markers are obtained from circular Hough transform and background markers from distance transform. The plasmodium infected RBCs are then detected in the Hue-Saturation-Intensity (HSI) color space. Thresholding on hue component of HSI color space is used to detect the chromatin dots of the parasite. Plasmodium falciparum and plasmodium vivax, the two dominant plasmodium species which cause the vast deaths in Ethiopia, are differentiated based on the size of infected RBCs. The performance of the proposed system for RBC segmentation, parasite detection and species differentiations was analyzed by comparing with the gold standard manual method for the total of 91 images of thin blood smears. The result shows that 97% of the RBC counts are similar to the gold standard with 97.5% sensitivity and 84.4% positive predictive value for plasmodium parasite detection at the cellular level. The species differentiations were done for each image with the accuracy level of 91.46%. The result showed the potential of the method for supporting the mass screening of malaria parasite.

关键词： Digital Microscope Plasmodium Thin Blood Smears watershed algorithm Circular Hough Transform Distance Transform Hue-Saturation-Intensity (HSI) Thresholding

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Automatic Detection of Malaria Parasite based on Microscopic Image Analysis

Automatic Detection of Malaria Parasite based on Microscopic...

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作者： Abebe Bekele Addis Ababa University

学位级别：硕士

关键词： Digital Microscope Plasmodium Thin Blood Smears watershed algorithm Circular Hough Transform Distance Transform Hue-Saturation-Intensity (HSI) Thresholding

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Research and Implementation of Conglutinated Macrophage Image Segmentation Based on Improved watershed algorithm

Research and Implementation of Conglutinated Macrophage Imag...

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International Conference on Automation, Communication, Architectonics and Materials

作者： Wang, Ping Chen, Rong Luo, Wei Xia, Ruihua Nanchang Univ Dept Elect Informat Engn Nanchang Jiangxi Peoples R China JiangXi Branch China Eastern Airlines JiangXi Peoples R China

ISBN: (纸本)9783037851036

In the process of macrophage image manufacture, cell adhesion often appears because of equipment or man-made reason and then influences subsequent automatic detection and analysis. The traditional watershed algorithm is easy to cause over-segmentation for the volatility of gray extremum. To overcome these phenomena, an improved watershed algorithm which was based on macrophages image segmentation was introduced in this paper. The simulation results show that the improved algorithm can effectively segment adhesive macrophages and restrain the over-segmentation phenomena with an acceptable computation speed.

关键词： distance transformation watershed algorithm image segmentation over-segmentation

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AORTA SEGMENTATION USING THE watershed algorithm FOR AN AUGMENTED REALITY SYSTEM IN LAPAROSCOPIC SURGERY

AORTA SEGMENTATION USING THE WATERSHED ALGORITHM FOR AN AUGM...

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18th IEEE International Conference on Image Processing (ICIP)

作者： Lopez-Mir, F. Naranjo, V. Angulo, J. Villanueva, E. Alcaniz, M. Lopez-Celada, S. Univ Politecn Valencia Inst Interuniv Invest Bioingn & Tecnol Orientada Camino Vera S-N Valencia 46022 Spain MINES Paristech Ctr Morphol Math Math Syst Paris France Hosp Clin Benidorm Unidad Resonancia Magnet INSCANNER Benidorm Spain

ISBN: (纸本)9781457713033

This paper presents an algorithm for a 3D segmentation of the aorta artery in magnetic resonance images (MRI). The purpose is to project the 3D segmented aorta in the patient's abdomen with an augmented reality (AR) system to help the surgeon in laparoscopic interventions. In order to obtain accurate results in the segmentation process a marker-controlled watershed algorithm is used. Since this method requires a robust gradient image and two marker sets, a preprocessing step is carried out in each image. The algorithm is automatic and the results and promising with a Jaccard coefficient (JC) of 0.8107 +/- 0.0228.

关键词： medical image processing aorta segmentation mathematical morphology watershed algorithm augmented reality

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Novel watershed algorithm for Touching Rice Image Segmentation

Novel Watershed Algorithm for Touching Rice Image Segmentati...

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The 2011 International Conference on Advanced Materials and Information Technology Processing(AMITP 2011)

作者： Kuang Fang-Jun Xu Wei-Hong Wang Yan-Hua School of Computer Science and Technology Nanjing University of Science and Technology Department of Computer Science and Technology Hunan Vocational Institute of Safety and Technology College of Computer and Communications Engineering Changsha University of Science and Technology

ISBN: (纸本)9783037851579

An efficient watershed algorithm is proposed in order to solve the problem that touching rice is difficult to process during consequent image segmentation. First, the binary image is ultra-eroded by using a different structuring element to form different distance image. Second, watershed image is obtained by using the watershed algorithm. Finally, the real watershed can be extracted. Compared with other watershed algorithms, the experiment results demonstrated that this method segmented out rice successfully in the touching rice image and improved the measurement accuracy, and also overcome over-segmentation effectively.

关键词： watershed algorithm distance transformation ultra-erosion image segmentation real watershed touching rice

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Using a Method Based on a Modified K-Means Clustering and Mean Shift Segmentation to Reduce File Sizes and Detect Brain Tumors from Magnetic Resonance (MRI) Images

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WIRELESS PERSONAL COMMUNICATIONS 2016年第3期89卷 993-1008页

作者： Kim, JiHoon Lee, Sanghun Lee, GangSeong Park, YoungSoo Hong, YeongPyo Kwangwoon Univ Dept Plasmabiodisplay Seoul 139701 South Korea Kwangwoon Univ Dept Gen Educ 20 Kwangwoon Ro Seoul 139701 South Korea Int Univ Korea Dept Hosp Management Jinju 459721 South Korea

In this paper, we propose a method of elaborating and detecting brain tumor from MRI suitable for information sharing via the internet for a healthcare provider. This method allows for reducing image sizes without reducing the information content of the images in terms of detecting tumors. The proposed method involves first clarifying the brain tumor area using a modified K-means clustering method and initial segmentation using mean shift segmentation. Then a threshold setting is used to convert the gray scale image and remove noise by applying an erode operation. Finally, the brain tumors in the images are detected using a watershed algorithm. The proposed method was compared with two well-known methods namely the conventional K-mean clustering and Fuzzy C Means (FCM) clustering. We verified the precision and the objectivity of our proposed method. The average precision and recall for our proposed method were excellent with values of 0.914052 and 0.995641, respectively. Our method detected more brain tumors than the conventional K-means clustering and FCM clustering methods and was able to provide for an efficient image data processing with reduced file sizes.

关键词： IoT MRI K-means clustering Fuzzy C Means clustering Mean shift segmentation watershed algorithm

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Multi-focus image fusion algorithm based on focused region extraction

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NEUROCOMPUTING 2016年第PartB期174卷 733-748页

作者： Zhang, Baohua Lu, Xiaoqi Pei, Haiquan Liu, He Zhao, Ying Zhou, Wentao Shanghai Univ Sch Comp Engn & Sci Shanghai 200444 Peoples R China Inner Mongolia Univ Sci & Technol Sch Informat Engn Baotou 014010 Peoples R China

Detection of the focused region is the key issue of the multi-focus image fusion algorithm. The blurred boundary of the focused region increases the difficulty of identifying focused regions accurately. According to the principles that the focused region of the source image should be directly fused as much as possible, this paper proposes a novel multi-focus image fusion algorithm based on saliency analysis, Graph-based visual saliency (GBVS) algorithm is used to locate the focused region in the source image. Then, watershed and morphological methods are used to get the enclosed region of the saliency map and remove the pseudo-focus region. Finally, the focused region is fused directly and the remaining regions are fused based on the Shearlet transform. Experiments demonstrate that the proposed approach can accurately extract the focused region, the fused image preserves more features and it is superior to traditional methods in subjective and objective evaluations. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Multi-focus image fusion Saliency analysis watershed algorithm Shearlet transform

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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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Classification Method Research of Fresh Agaricus Bisporus Based on Image Processing

Classification Method Research of Fresh Agaricus Bisporus Ba...

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The International Conference on Intelligent Agriculture 2017(ICIA2017)

作者： Fengyun Wang Jiye Zheng Lei Wang Wenjie Feng Luyan Niu S＆T Information Institute Shandong Academy of Agricultural Sciences

The article studies the classification method for the fresh agaricus bisporus based on image processing. When acquiring the image information, the shadow of image and mushroom stipe may affect the analysis of maximum diameter of agaricus bisporus which is the important factor. In this paper, the global threshold segmentation method and maximum entropy threshold segmentation method are combined to carry out the first watershed algorithm to remove the shadow of image. Then the Canny operator, opening and closing operation and corrosion expansion are used to carry out the second watershed algorithm for the removal of stipe interference. The method achieves a good result through the comparison between the actual measured results and experimental results.

关键词： Agaricus bisporus Image processing Maximum entropy threshold segmentation watershed algorithm

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