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Improved segmentation of low-contrast lesions using sigmoid edge model

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY 2016年第7期11卷 1267-1283页

作者： Foruzan, Amir Hossein Chen, Yen-Wei Shahed Univ Fac Engn Dept Biomed Engn Tehran Iran Ritsumeikan Univ Coll Informat Sci & Engn Intelligent Image Proc Lab Kusatsu Shiga Japan

The intensity profile of an image in the vicinity of a tissue's boundary is modeled by a step/ramp function. However, this assumption does not hold in cases of low-contrast images, heterogeneous tissue textures, and where partial volume effect exists. We propose a hybrid algorithm for segmentation of CT/MR tumors in low-contrast, noisy images having heterogeneous/homogeneous or hyper-/hypo-intense abnormalities. We also model a smoothed noisy intensity profile by a sigmoid function and employ it to find the true location of boundary more accurately. A novel combination of the SVM, watershed, and scattered data approximation algorithms is employed to initially segment a tumor. Small and large abnormalities are treated distinctly. Next, the proposed sigmoid edge model is fitted to the normal profile of the border. The estimated parameters of the model are then utilized to find true boundary of a tissue. We extensively evaluated our method using synthetic images (contaminated with varying levels of noise) and clinical CT/MR data. Clinical images included 57 CT/MR volumes consisting of small/large tumors, very low-/high-contrast images, liver/brain tumors, and hyper-/hypo-intense abnormalities. We achieved a Dice measure of and average symmetric surface distance of mm. Regarding IBSR dataset, we fulfilled Jaccard index of . The average run-time of our code was s. Individual treatment of small and large tumors and boundary correction using the proposed sigmoid edge model can be used to develop a robust tumor segmentation algorithm which deals with any types of tumors.

关键词： Sigmoid edge model Scattered data approximation Tumor segmentation watershed algorithm Medical image processing

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3D reconstruction method based on contour features

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Journal of Beijing Institute of Technology 2016年第3期25卷 301-308页

作者： HAN Bao-ling ZHU Ying LUO Qing-sheng XU Bo ZHANG Tian School of Mechanical Engineering Beijing Institute of Technology Beijing 100081 China School of Optoelectronics Beijing Institute of Technology Beijing 100081 China School of Mechatronical Engineering Beijing Institute of Technology Beijing 100081 China

To guarantee the accuracy and real-time of the 3D reconstruction method for outdoor scene,an algorithm based on region segmentation and matching was ***,on the basis of morphological gradient information,obtained by comparing color weight gradient images and proposing a multi-threshold segmentation,scene contour features were extracted by a watershed algorithm and a fuzzy c-means clustering ***,to reduce the search area,increase the correct matching ratio and accelerate the matching speed,the region constraint was established according to a region＇s local position,area and gray characteristics,the edge pixel constraint was established according to the epipolar constraint and the continuity ***,by using the stereo matching edge pixel pairs,their 3D coordinates were estimated according to the binocular stereo vision imaging *** results show that the proposed method can yield a high stereo matching ratio and reconstruct a 3D scene quickly and efficiently.

关键词： gradient map watershed algorithm fuzzy c-means clustering algorithm region con-straint contour matching 3D reconstruction

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Automatic Segmentation Method of Touching Corn Kernels in Digital Image Based on Improved watershed algorithm

Automatic Segmentation Method of Touching Corn Kernels in Di...

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2011 International Conference on New Technology of Agricultural Engineering(ICAE 2011)

作者： Quan Longzhe Engineering College of Engineering Northeast Agricultural University Harbin,china Jiang Enchen Engineering College of Engineering Northeast Agricultural University Harbin,china

in order to separate touching corn kernels in digital image,this paper made the improvement to the watershed algorithm,this improved method can resolve the problems of 'algorithm-over-segmentation'and'leakage',and realized automatic segmentation of touching corn ***,in order to get the pretreatment image,Wiener filter and mathematical morphology were adopted to reduce noises and clarify background of the image;secondly,by combining with tow edge detection operators,the boundary of touching corn kernels was determined in the image,which can serve as watershed of the algorithm;thirdly,erode transform was used to construct basin of the algorithm;at last,the algorithm of purifying image background was proposed,solving the problem of'leakage'.The results of experiment showed that the correction rate of segmentation is 94%by this automatic segmentation method.

关键词： corn kernels Touching automatic segmentation method watershed algorithm

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Adaptive striping watershed segmentation method for processing microscopic images of overlapping irregular-shaped and multicentre particles

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JOURNAL OF MICROSCOPY 2015年第1期258卷 6-12页

作者： Xiao, X. Bai, B. Xu, N. Wu, K. Tsinghua Univ State Key Lab Precis Measurement Technol & Instru Dept Precis Instrument Beijing 100084 Peoples R China Tsinghua Univ Shenzhen Grad Sch Shenzhen 518057 Peoples R China

Oversegmentation is a major drawback of the morphological watershed algorithm. Here, we study and reveal that the oversegmentation is not only because of the irregular shapes of the particle images, which people are familiar with, but also because of some particles, such as ellipses, with more than one centre. A new parameter, the striping level, is introduced and the criterion for striping parameter is built to help find the right markers prior to segmentation. An adaptive striping watershed algorithm is established by applying a procedure, called the marker searching algorithm, to find the markers, which can effectively suppress the oversegmentation. The effectiveness of the proposed method is validated by analysing some typical particle images including the images of gold nanorod ensembles.

关键词： Image processing particle image segmentation watershed algorithm

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Comprehensive Applying watershed algorithm in Segmentation of CT Brain Images

Comprehensive Applying Watershed Algorithm in Segmentation o...

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2011 6th IEEE Joint International Information Technology and Artificial Intelligence Conference(ITAIC 2011)

作者： ZHU Bing-li Experimental Center Chongqing Three Gorges University,CTGU Wanzhou,Chongqing,China Xiong Jiang College of Mathematics and Computer Science Chongqing Three Gorges University,CTGU Wanzhou,Chongqing,China Tan Xiao-ling College of Physics and Electronic Engineering Chongqing Three Gorges University,CTGU Wanzhou,Chongqing,China

According to the multi-threshold values of CT brain images,applying watershed segmentation algorithm by comprehensive methods which take full advantage of de-noising,gradient reconstruction,watershed segmentation,binary result and so *** the binary skull image that is good at de-noising,detail accepting and over segmentation *** the program designed in MATLAB can process batches of CT brain images effectively,moreover,it can gain prophase data that is useful in anaphase image processing.

关键词： CT brain image image segmentation multi-threshold values watershed algorithm MATLAB

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An Object-oriented Extraction Method of Arable Land Information based on a Combination of watershed and Multi-scale

An Object-oriented Extraction Method of Arable Land Informat...

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International Conference on Intelligent Earth Observing and Applications (IEOAs)

作者： Li, Jingwen Lv, Nan Zhou, Song Li, Wenqing Guo, Weili Guilin Univ Technol Coll Geomat & Geoinformat Guilin City 541004 Guangxi Provinc Peoples R China Guangxi First Mapping Inst Nanning 530023 Guangxi Provinc Peoples R China

ISBN: (纸本)9781510600492

Based on analyzing the multi-scale segmentation technique of watershed transform, by combining the multiple features of textured images, spectra and shape, an integrated image segmentation method of a combination of watershed and multi-scale can be presented. This article is combined with object-oriented technology, and applied it to extracting the information of arable land in Guangxi. The paper aims to establish classification system to solve the problem of extracting feature information by extracting the feature or feature combination of the class. The experimental result showed that the object-oriented extraction method of arable land information based on a combination of watershed and multi-scale could be better to realize extract and apply the information of high resolution remote sensing image.

关键词： Image segmentation watershed algorithm multi-scale segmentation arable land information extraction object-oriented high spatial resolution image

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Geometric Parameter Visual Detection for Laser Fracture Splitting Groove of the Engine Connecting Rod

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JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE 2015年第9期12卷 2769-2775页

作者： Liu, Changying Liu, Yang Chu, Xinze Wang, Tianhao Cai, Wenjing Jilin Univ Coll Instrumentat & Elect Engn Changchun 130061 Peoples R China Jilin Univ Coll Automot Engn Changchun 130061 Peoples R China

The connecting rod is one of the main transmission parts of an automobile engine, and the connecting rod fracture splitting technology directly affects the overall performance of the engine. The processing quality of the laser fracture splitting of the connecting rod also directly influences the effect of the connecting rod's fracture splitting processing technology. In this article, we present an online, machine vision-based method for outline dimension detection of the laser fracture splitting groove of the engine connecting rod. The image of the laser fracture splitting groove of the connecting rod was acquired with a camera, followed by the application of an adaptive threshold-based Otsu algorithm for image and background segmentation. A multi-scale watershed algorithm for image edge segmentation and fitting processing was employed to obtain the final detection information by characteristic parameter extraction method. The experimental results demonstrate the feasibility of the method presented in the paper. The detection precision was found to meet the requirements of the fracture splitting processing technology for automobile connecting rods.

关键词： Automobile Connecting Rod Machine Vision Ttireshold Segmentation watershed algorithm

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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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Probability of failure of the watershed algorithm for peak detection in comprehensive two-dimensional chromatography

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JOURNAL OF CHROMATOGRAPHY A 2010年第8期1217卷 1375-1385页

作者： Vivo-Truyols, Gabriel Janssen, Hans-Gerd Univ Amsterdam Analyt Chem Grp vant Hoff Inst Mol Sci NL-1018 WV Amsterdam Netherlands Unilever Res Labs Adv Measurement & Data Modelling NL-3130 AC Vlaardingen Netherlands

The watershed algorithm is the most common method used for peak detection and integration In two-dimensional chromatography However, the retention time variability in the second dimension may render the algorithm to fail A study calculating the probabilities of failure of the watershed algorithm was performed The main objective was to calculate the maximum second-dimension retention dine variability. Delta(2)t(Rcut). above which the algorithm fails Several models to calculate Delta(2)t(Rcut) were developed and evaluated (a) exact model. (b) simplified model and (c) simple-modified model Model (c) gave Isle best performance anti allowed to deduce an analytical expression for the probability of failure of the water shed algorithm as a function of experiment al Delta(2)t(R). modulation time anti peak width in the first and second dimensions It could be demonstrated that The probability of failure of the watershed algorithm under normal conditions in GC x GC Is around 15-20% Small changes of Delta(2)t(R), modulation time and/or peak width in the first anti second dimension could Induce subtle changes in the probability of failure of the watershed algorithm Theoretical equations were verified with experimental results from a diesel sample injected in GC x GC and were found to be ill good agreement with the experiments (C) 2009 Elsevier 13 V All I fights reserved

关键词： Two-dimensional chromatography watershed algorithm Peak detection

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BIRD'S-EYE VIEW IMAGES TAKEN PLANT MATERIAL AND COUNTING 23

BIRD'S-EYE VIEW IMAGES TAKEN PLANT MATERIAL AND COUNTING

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23nd Signal Processing and Communications Applications Conference (SIU)

作者： Karhan, Zehra Karakaya, Aykut Senyer, Nurettin Kayhan, Gokhan Ondokuz Mayis Univ Bilgisayar Muhendisligi Bolumu Samsun Turkey

ISBN: (纸本)9781467373869

In this study, the recognition of agri-food plants out of the images obtained by the UAV and are intended to implement the counting process. Images obtained with the UAV from plants separation from the background;K-Means (K-Means) with the help of visual elements in the classifier was classified as soil and plants. A better image segmentation and noise in the resulting plants were made to eliminate the morphological filtering. The plants on the noise-free image separation nested data for individual numbers of watershed algorithm was applied. To represent the resulting plant was subjected to the binary image acquisition and counting process. Plant identification methods applied and the counting process accuracy and 87.7% sensitivity, 86.6% were found to implement.

关键词： K-means algorithm Morphological filtering watershed algorithm

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