检索结果-内蒙古大学图书馆

Automatic extraction of infrared small target based on support vector regression and adaptive region growing algorithm

引用

OPTICAL ENGINEERING 2007年第4期46卷

作者： Liu, RuiMing Yang, Lei Liu, Erqi Yang, Jie Li, Ming Wang, Fanglin Shanghai Jiao Tong Univ Inst Image Proc & Pattern Recognit Shanghai 200240 Peoples R China China Aerosp Sci & Ind Corp Inst Second Acad Beijing 100854 Peoples R China

A region-growing algorithm requires knowledge of the position of seed points in advance and must prespecify a threshold for the homogeneity test. Thus, the process of image segmentation by this algorithm cannot be implemented automatically, which often restricts its application in engineering practice. We propose an adaptive region-growing algorithm for automatically extracting small targets from an IR image. Using support vector regression (SVR), seed points can be detected automatically by regarding the intensity of an image as a surface. Furthermore, an adaptive threshold function is given as the criterion of the homogeneity test instead of a fixed threshold, as used in conventional region-growing algorithms. Our technique can extract small targets without human intervention. We carefully design many experiments to demonstrate its validity in extracting IR small targets. (C) 2007 Society of Photo-Optical Instrumentation Engineers.

关键词： region growing algorithm support vector regression median filter high-pass filter

来源：评论

学校读者我要写书评

暂无评论

Lung tumor segmentation using improved region growing algorithm

引用

NUCLEAR ENGINEERING AND TECHNOLOGY 2020年第10期52卷 2313-2319页

作者： Soltani-Nabipour, Jamshid Khorshidi, Abdollah Noorian, Behrooz Islamic Azad Univ Med Radiat Engn Dept Parand Branch Parand Iran Gerash Univ Med Sci Sch Paramed Gerash Iran Grad Univ Adv Technol Fac Elect & Comp Engn Nucl Engn Dept Kerman Iran

The goal of this project is to achieve an accurate segmentation of the pulmonary tumors besides shortening the time and increasing the accuracy. Here, improved region growing (IRG) algorithm is introduced in order to segment the lung tumor with a sufficient accuracy in a shorter time compared to the other basics methods. This comprehensive algorithm was applied on 4 patients CT images and the results of the various steps on segmentation improvement shown 98% accuracy as compared to the basic algorithm. The combination of "multipoint growth start" produced a desirable outcome in accurately bounding the tumor. The proposed algorithm improved tumor identification by less than 13% along with a sufficient percentage of compliance accuracy. (c) 2020 Korean Nuclear Society, Published by Elsevier Korea LLC. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： region growing algorithm Automatic thresholding Tumor boundaries Accuracy CT slices

来源：评论

学校读者我要写书评

暂无评论

A Novel Approach for Detecting the Tumor Size and Bone Cancer Stage using region growing algorithm 7

A Novel Approach for Detecting the Tumor Size and Bone Cance...

引用

7th International Conference on Computational Intelligence and Communication Networks (CICN)

作者： Reddy, Kishor Kumar C. Anisha, P. R. Raju, G. V. S. Stanley Coll Engn & Tech Women Hyderabad Andhra Pradesh India

ISBN: (纸本)9781509000760

Cancer has been a plague in our society since the dawn of recorded history. The radical surgical resection represents the only chance for cure but, unfortunately it is possible in only 15% of patients. Even at experienced centres the 5-year survival rates for the most favourable patients who undergo resection and adjuvant therapy are less than 20%. In this paper, a methodology is proposed for identifying the tumor size and based on the size, the stage of the cancer is identified. The methodology involves scanned images captured at various locations of the human body which are collected from different diagnostic labs. Based on region growing algorithm the segmentation is carried out to analyze the tumor part via which the size of the tumor and the stage at which the tumor relies is empirically calculated.

关键词： Cancer region growing algorithm Tumor Size

来源：评论

学校读者我要写书评

暂无评论

Comparisons of Planar Detection for Service Robot with RANSAC and region growing algorithm 36

Comparisons of Planar Detection for Service Robot with RANSA...

引用

第36届中国控制会议

作者： Zhijun Zhang Yongqian Huang Wenkang Zhang Jiawei Luo IEEE The School of Automation Science and Engineering South China University of Technology Pingxiang University

ISBN: (纸本)9781538629185

Considering the life independence of people with disabilities or a limited range of movement,we intend to develop an intelligent mobile service robot equipped with robot manipulator and computer *** order to implement an automatic moving,grasping and delivering task,the abilities of service robot to deal with the images they see and collect useful information are really *** this paper,two different algorithms(i.e.,the RANSAC algorithm and the region growing algorithm)of the planar detection for the service robot are introduced with detailed principles and implementation *** the foundation of our mobile service robot's development,three specific experiments are designed to compare the algorithms on accuracy,robustness and computational ***,after the comparison between two algorithms,the suitability of two algorithms for the service robot using in the environment detection will be presented and analyzed.

关键词： Service Robot Computer Vision Planar Detection 3D Point Cloud Ransac algorithm region growing algorithm

来源：评论

学校读者我要写书评

暂无评论

Steel plate corrugation defect intelligent detection method based on picture cropping and region growing algorithm 14

Steel plate corrugation defect intelligent detection method ...

引用

14th IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Li, Leyang Hao, Peifeng Northeastern Univ Software Coll Shenyang Peoples R China

ISBN: (纸本)9781538694909

In the continuous casting production process, defect detection of surface corrugation is a key process to ensure the quality of the hot rolled sheet products in the subsequent process. Currently, the manual detection approaches used in most steel productions inevitably causes an ineffectiveness and inefficiency. Accordingly, an effective detection method is urgently needed to identify the defections of steel plate corrugations. Aiming at this problem, this paper designs a new defect detection method based on image cropping and region growing algorithm, which uses image detection technology to detect steel plate ripple and to determine whether there is a defect. First, based on a detailed analysis of the steel plate surface defects, we combine the image cropping with improved region growing algorithm to deal with the defect image. Especially, the portion with no defects is cut from in its image by image cropping algorithm, and then the rest are detected by the region growing algorithm. Finally, this algorithm is validated on steel plate data sets. Experimental results show that the proposed algorithm performs powerfully, obtaining a higher recognition rate. That means this algorithm is an effective intelligent detection tool to replacing traditional manual recognition in some ways.

关键词： defect detection picture cropping region growing algorithm

来源：评论

学校读者我要写书评

暂无评论

A Novel Methodology to Detect Bone Cancer Stage Using Mean Intensity of MRI Imagery and region growing algorithm 1

引用

International Congress on Information and Communication Technology (ICICT)

作者： Balachandrudu, K. E. Reddy, C. Kishor Kumar Raju, G. V. S. Anisha, P. R. Malla Reddy Inst Engn & Technol Hyderabad Andhra Pradesh India Stanley Coll Engn & Technol Women Hyderabad Andhra Pradesh India

ISBN: (数字)9789811007552

ISBN: (纸本)9789811007552;9789811007545

Cancer has been a plague in our society since the dawn of recorded history. The radical surgical resection represents the only chance for cure but, unfortunately it is possible in only 15 % of patients. Even at experienced centers the 5 year survival rates for the most favorable patients who undergo resection and adjuvant therapy are less than 20 %. In this paper, a methodology is proposed for identifying the bone cancer affected part. The methodology involves scanned images captured at various locations of the human body which are collected from different diagnostic labs. Based on region growing algorithm, the segmentation is carried out to analyze the tumor part through which the intensity of cancer and the stage at which the tumor relies is empirically calculated.

关键词： Bone cancer Gray scale Mean intensity Segmentation region growing algorithm Tumor

来源：评论

学校读者我要写书评

暂无评论

An analytical proof on suitability of Cauchy-Schwarz Divergence as the aggregation criterion in region growing algorithm

引用

IMAGE AND VISION COMPUTING 2021年 115卷

作者： Baleghi, Yasser Rousseau, David Babol Noshirvani Univ Technol Dept Elect & Comp Engn Shariati St Babol Iran Univ Angers UMR INRAE IRHS LARIS 62 Ave Notre Dame Lac F-49000 Angers France

region growing algorithm (RGA) isa popular, fast and strongly formed object segmentation method. In RGA, the region is grown from the seed points to adjacent points depending on an aggregation criterion. Despite the huge literature on RGA, none of the proposed aggregation criteria have been analytically proved to be suitable for an ideal segmentation. In this paper, Cauchy-Schwarz Divergence (CSD) is proved to be suitable as an aggregation criterion in RGA for object segmentation. First, RGA is formulated in this context. The Cauchy-Schwarz-based cri-terion is proposed here in the continuous case for a bimodal image that contains one object in the background while both regions are normally distributed with different parameters (while the assumption of normal distribu-tion of object and background has been used by many researchers in minimum error thresholding method). Then, a proof is given that in the mentioned formulated case, the proposed RGA will lead to an ideal segmenta-tion. The case is also investigated while object and background have heavy-tail distributions like generalized Gaussian function when beta < 2. While all formulations and proofs are given in the continuous case, the segmen-tation results in the discrete case are shown to be good. Comparison of these results with the outcomes of RGA with traditional aggregation criteria, shows how analytical justifications can suggest a better criterion. (c) 2021 Elsevier B.V. All rights reserved.

关键词： region growing algorithm Image segmentation Cauchy-Schwarz divergence Aggregation criterion

来源：评论

学校读者我要写书评

暂无评论

Microarray Image Segmentation Using region growing algorithm and Mathematical Morphology

Microarray Image Segmentation Using Region Growing Algorithm...

引用

The Fifth International Conference on Information Assurance and Security(第五届信息保障与安全国际会议)

作者： Ping YE Guirong WENG School of Mechanical & Electrical Engineering Soochow University Suzhou China

ISBN: (纸本)9780769537443

Image processing is an important aspect of microarray experiments. Spots segmentation meaning to distinguish the spot signals from background pixels, is a critical step in microarray image processing. After analyzing other existing means of microarray segmentation, a new method based on region growing algorithm, mathematical morphology (MM) filtering and morphological processing is presented. And its corresponding theory and realizable steps are introduced in this paper. The simulations show that the region growing algorithm method for spot image segmentation has better performance than the most commonly used segmentation methods including the ScanAlizeTM method and GenePixTM method. The Experimental results are computationally attractive, have excellent performance and can preserve structural information while efficiently suppressing noise in cDNA microarray data.

关键词： mathematical morphology region growing algorithm microarray image segmentation Image processing

来源：评论

学校读者我要写书评

暂无评论

region of Interest Extraction of Medical Image based on Improved region growing algorithm

Region of Interest Extraction of Medical Image based on Impr...

引用

2017 International Conference on Material Science,Energy and Environmental Engineering(MSEEE 2017)

作者： Shanshan Sun Runtong Zhang School of Economics and Management Beijing Jiaotong University

ISBN: (纸本)9781510847002

Medical images are usually made up of regions of interest(ROI) and background areas, relative to the background area, the ROI contains important diagnostic *** the ROI may not be large in the entire image area, it is of great significance for doctors' diagnosis, clinical treatment and pathological *** purpose of the paper is to extract the ROI from the surrounding environment by extracting the features of the Medical *** paper is aimed at splitting the medical image by combining iteration algorithm and region growing algorithm, thus can mark out the nidus clearly.

关键词： Medical Image region of interest iteration algorithm region growing algorithm

来源：评论

学校读者我要写书评

暂无评论

Defect identification of fan blade based on adaptive parameter region growth algorithm

引用

SCIENTIFIC REPORTS 2025年第1期15卷 1-14页

作者： Wang, Yifan Wang, Xueyao Yang, Dongmei Ru, Xinqin Zhang, Yuxin North China Elect Power Univ Sch Control & Comp Engn Beijing 102206 Peoples R China NARI Grp Corp State Key Lab Smart Grid Protect & Control Nanjing 211106 Peoples R China

China's wind power generation is rich in resources and mature technology, but has the problems of harsh power generation environment, high operation and maintenance costs due to complex operating conditions, and serious consequences of failures. For this reason, this paper proposes a more efficient defect identification method for wind turbine blades that have the longest downtime due to faults. Firstly, starting from the characteristics that the blade defects are darker than the surrounding and distributed in block or point shape, the blade images taken by UAV cruise are processed by grey scaling, filtering, histogram equalization and Grab-cut foreground segmentation. Secondly, a wind turbine blade defect recognition algorithm based on the adaptive parameter region growth algorithm is proposed, where the number of seed selection points and location information are planned through the results of image preprocessing and the conventional defect features of wind turbine blades;and a threshold adapted to a variety of defects is determined through the results of filtering and equalization. Finally, the image of defect recognition is demonstrated through morphological algorithm and framing optimization, the Mean Intersection over Union (MIoU) performance evaluation index is analyzed, and the effectiveness of the algorithm is verified through experimental data comparison.

关键词： Wind power generation Fan blade Defect identification Adaptive parameters region growing algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：