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2014 IEEE Computers,Communications and IT Applications Conference(ComComAp)

作者： Li Pengfei Meng Qi Zhang Weihong Bei Hang University Xi Dian University

ISBN: (纸本)9781479948109

Edge detection and segmentation of binary image are used in estimation of the number of several kinds of crop *** available method of segmentation of background and foreground is *** solve the problem of oversegmentation,an improved watershed algorithm to the crop seeds image with the edge information is *** indicate that the method not only overcomes over-segmentation,but improves the precision of ***,area algorithm is appended to correct count number,which improves the accuracy of count number.

关键词： Image Segmentation Edge Detection watershed algorithm Area algorithm

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Automatic Image Segmentation Using Edge and Marker-Controlled watershed Transformation

Automatic Image Segmentation Using Edge and Marker-Controlle...

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International Conference on Advances in Engineering and Technology (ICAET’2014, Singapore)

作者： Khin Lay Mon the University of Computer Studies Mandalay

Image segmentation has been a difficult task in computer vision. The role of image segmentation is to decompose an image into parts that are meaningful with respect to the particular applications. Subsequent methods for image description, recognition, image visualization, image compression, highly depend on the segmentation results obtained from previous stage. Therefore, we propose an automatic image segmentation method by combining an edge detection technique with modified mask as a preprocessing method and Marker Controlled watershed Transformation（MCWT） for final image segmentation. In this paper, watershed algorithm with modified Laplacian of Gaussian（LoG） edge detector is used to detect the gradient image of input image and produce the image which is less sensitive to noise. In order to get final image with less over segmentation, it is helped by MCWT. Therefore, our proposed method has also been observed a satisfactory segmentation image with better edges and with less over segmentation.

关键词： Laplacian of Gaussian filter Zero Crossing watershed algorithm Marker-controlled watershed Transformation

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The Segmentation of Overlapping Milk Somatic Cells Based on Improved watershed algorithm

The Segmentation of Overlapping Milk Somatic Cells Based on ...

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International Conference on Artificial Intelligence and Computational Intelligence

作者： Na, Su Heru, Xue Inner Mongolia Agr Univ Coll Comp & Informat Engn Hohhot Peoples R China

ISBN: (纸本)9780769538167

In view of the shape irregularity and the stack phenomenon in milk somatic cell pictures. An improvement watershed method is proposed in the paper, which is mainly used in resolving the over-segmentation problem in watershed algorithm. Its main idea is: distance transformation is used for binary image firstly, obtaining the central points in the local maximum regions (seed points), and merging the redundancy seed points. This makes the over-segmentation problem was basically solved. Finally the small areas are deleted after watershed segmentation. Experiments show that the improved watershed method can accurately and quickly separate the milk somatic cells and control the over-segmentation. The effect is obvious.

关键词： watershed algorithm image segmentation cell separation milk somatic cell

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Implement for Stomach Epidermis Tumor Diagnosis Based on watershed algorithm and Boundary Tracing algorithm

Implement for Stomach Epidermis Tumor Diagnosis Based on Wat...

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3rd International Symposium on Intelligent Information Technology Application

作者： Li, Guangli E China Jiaotong Univ Sch Informat Engn Nanchang Peoples R China

ISBN: (纸本)9780769538594

Image segmentation is a key process of any image recognition system. Loose repeat algorithm and K-means algorithm are used to resolve the stomach epidermis tumor segmentation, but many conglutinated cells cannot be separated by others with the help of traditional segmentation algorithms. So the Vincent watershed algorithm as well as the Inver watershed algorithm is designed to do segmentation experiments about stomach epidermis tumors. A lot of experiments about several kinds' images were done to build the right segmentation theory. The conclusion of these experiments show that these two algorithms could get good segmentation results while the image has few conglutinated ***, the Inver algorithm may get better result than the Vincent algorithm while the image has many conglutinated areas. As a defect of the Inver algorithm, it may take many very small areas after segmentation. Finally, boundary tracing algorithm is designed to obtain the boundaries of tumor cells.

关键词： stomach epidermis tumor image segmentation watershed algorithm conglitunated areas boundary tracing algorithm

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Study of FPGA-based Visual Detection for Pointer Dial

Study of FPGA-based Visual Detection for Pointer Dial

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第26届中国控制与决策会议

作者： Bin Sun Changsheng Zhang Ziyu Liu Bin Qian HanPing Zhang Faculty of Information Engineering and Automation Kunming University of Science and Technology

The lubricating oil pressure of ball mill in ore dressing plant is a critical real-time monitoring parameter. In this paper, bilinear interpolation, DoG filter, Marr-Hildreth edge detector and watershed algorithms are studied on FPGA. In particular, the algorithm HVPP is proposed. Segmentation, extraction and number identification are realized for the pressure pointer dial image by using these algorithms, such that intelligent reading for the gauge is achieved. Experiment shows that employing the fast algorithm based on logic circuit to accomplish the machine recognition has advantages of good real-time performance and high recognition rate.

关键词： Marr-Hildreth edge detector Bilinear interpolation watershed algorithm HVPP

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Image processing identification of laser damage induced by ns-pulsed lasers

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OPTIK 2013年第14期124卷 1940-1942页

作者： Han, Jinghua Li, Yaguo Duan, Tao He, Changtao Gao, Ya Feng, Guoying Yang, Liming Sichuan Univ Sch Elect & Informat Engn Chengdu 610064 Peoples R China Fine Opt Engn Res Ctr Chengdu 60041 Peoples R China Akita Prefectural Univ Dept Machine Intelligence & Syst Engn Yurihonjo 0150055 Japan Southwest Univ Sci & Technol Lab Extreme Condit Matter Properties Mianyang 621010 Peoples R China Univ Elect Sci & Technol China Sch Elect & Technol Chengdu 610051 Peoples R China

For the purpose of quantitatively evaluating laser-induced damage in optical glass, image processing was employed. The image processing involves an improved watershed segmentation algorithm, with the aid of which different morphologies of laser damage in glass were classified. The shapes and distribution of cracks can be readily discerned in the gradient image while the severity of damage is apparent in the gray-scale image after being filtered;in addition, the marker image can be utilized to recognize the region where the damage appears;the final segmentation embodies all characteristics of damaged area and is an effective means of analyzing the laser damage in optical glass. (C) 2012 Elsevier GmbH. All rights reserved.

关键词： Laser induced damage Image processing watershed algorithm Marker control

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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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Overlapping nuclei segmentation using direction-based flow tracking

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IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING 2013年第4期8卷 387-394页

作者： Surut, Yunyong Phukpattaranont, Pornchai Prince Songkla Univ Fac Engn Dept Elect Engn Hat Yai 90110 Songkhla Thailand

In medical image processing, the segmentation of overlapping nuclei is one of the challenging topics, which relates to its application in diagnostic pathology. To achieve the quantification accuracy (ACC) of the diagnosis, we propose an overlapping nuclei segmentation algorithm using the principle of direction-based flow tracking (DBFT). The DBFT, which consists of direction field preparation and direction field tracking, is performed to provide the direction field and the labeled distinct single nucleus. Its performance is validated with 6375 nuclei from 29 images and compared with two popular overlapping objects segmentation methods, i.e., traditional watershed (TWS) and marker-controlled watershed (MCWS). While the sensitivity (SS) of the DBFT, TWS, and MCWS is 0.981, 0.990, and 0.966, respectively, and the corresponding positive predictive value (PPV) is 0.948, 0.831, and 0.910. The ACC values and F1 measures obtained from the combination of SS and PPV are used as the total performance measures. While the ACC values from DBFT, TWS, and MCWS are 0.930, 0.824, and 0.882, respectively, the corresponding F1 measures are 0.964, 0.904, and 0.937. The results clearly show that the DBFT is the best among three methods because it provides the maximum numbers on both ACC and F1 values. (c) 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

关键词： image segmentation overlapping nuclei watershed algorithm marker-controlled watershed quantification accuracy

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Excellent side-to-side symmetry in glenoid size and shape

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SKELETAL RADIOLOGY 2013年第12期42卷 1711-1715页

作者： Shi, Lin Griffith, James F. Huang, Junbin Wang, Defeng Chinese Univ Hong Kong Dept Imaging & Intervent Radiol Shatin Hong Kong Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China

In quantifying glenoid bone loss and as a means to determine initial glenoid size, the abnormal glenoid is often compared with the contralateral normal glenoid. The assumption is that good symmetry exists between both glenoid surfaces with regard to size and shape. The purpose of this study is to critically analyze the structural symmetry of both glenoids in an objective and quantitative manner to ascertain the degree of symmetry present. The study cohort comprised 60 subjects (35 males and 25 females) with no shoulder pathology or injury. Each glenoid surface was extracted from the whole scapular model constructed from CT data using a 3D curvature-based incremental watershed algorithm. Glenoid morphometric analysis was carried out based on the 2D contour of the glenoid projected on the principal plane. There was no side-to-side difference in glenoid length (p = 0.53), width (p = 0.42), area (p = 0.36), or circumference (p = 0.73). All glenoid dimensions were larger in males than females (p < 0.05). Point-wise curvature analysis showed no significant shape difference between both glenoids (all p > 0.1). Regression analysis revealed a positive correlation (R (2) = 0.3-0.5) between increasing age and increasing glenoid size. In normal subjects, both glenoids are highly symmetric in shape and size. This study provides objective and quantitative justification for using the normal counterlateral glenoid as a reference standard for initial glenoid shape in patients with unilateral glenoid bone loss.

关键词： Computed tomography watershed algorithm Morphological analysis Glenoid Shoulder dislocation

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Listeria Monocytogenes Colony Counting from Microscopic Images using Nonlinear Piecewise Least-Square Curve-Fitting Filter

Listeria Monocytogenes Colony Counting from Microscopic Imag...

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4th International Conference on Information Science and Applications (ICISA)

作者： Pahnchawatt, Kitthichai Lipikorn, Rajalida Keeratipibul, Suwimon Chulalongkorn Univ Fac Sci Machine Intelligence & Multimedia Informat Techno Dept Math & Comp Sci Bangkok 10330 Thailand Chulalongkorn Univ Fac Sci Machine Intelligence & Multimedia Informat Techno Dept Food Technol Bangkok 10330 Thailand

ISBN: (纸本)9781479906048;9781479906024

This paper proposes a novel method to enhance out-of-focus regions in microscopic images and detect Listeria Monocytogenes(L. monocytogenes.) in biofilm on a conveyor belt from an image with the aim to count the colonies of L. monocytogenes. Consider that a microscope can focus on a single point in the sample, this limitation makes each image contain both in-focus and out-of-focus regions. These out-of-focus regions are blurred with different blurring scale, thus the proposed method uses nonlinear piecewise least-square curve-fitting filter and the gradient to enhance the out-of-focus regions. Finally, watershed algorithm and morphological operations are used to segment and count the colonies. The proposed method was evaluated on a set of 30 L. monocytogenes microscopic images and a set of 90 synthetic test images. The counting results reveal that our proposed method can improve the quality of an image by enhancing the out-of-focus regions while preserving other regions which leads to more accurate counting results.

关键词： Listeria monocytogenes colony counting nonlinear piecewise least-square curve-fitting filte watershed algorithm out-of-focus blurred images

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