检索结果-内蒙古大学图书馆

1st IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)

作者： Dong, Jiyang Xue, Jian Jiang, Shuqiang Lu, Ke Univ Chinese Acad Sci Sch Engn Sci Beijing Peoples R China Chinese Acad Sci Inst Comp Technol Beijing Peoples R China

ISBN: (纸本)9781538618578

segmentation is a very crucial step in many applications. Actually, there are often more than one object to be segmented in an image or a video. Taking the lung images as an example, pulmonary lesions area and lung parenchyma area are both important basis for a doctor to make diagnoses. Due to the fact that lung lesion areas and lung tissues have close gray values in the image, and the diversity, irregularity and location uncertainty of pulmonary lesions, traditional segmentation methods cannot segment objects of interest accurately, nor can extract them at the same time. In this paper, a novel approach is proposed for multiple objects segmentation based on Graph Cut. The algorithm introduces a multi-layers graph structure to represent different regions from inside to outside in an image. Besides, the foreground and background are modeled by Gaussian Mixture Models (GMMs) which can describe the gray distributions of them accurately. Then the weights of parts of links in the graph can be calculated by the probability distribution of the models. To solve the problem of boundaries leakage when two objects with similar gray value are in close proximity, a shape constraint is added to the energy function. The segmentation is achieved by max-flow/min-cut and all of the objects can be obtained. Experiment results demonstrate that the proposed method in this paper can deal with the CT images of lung with pathologies, and has accuracy and robustness.

关键词： multiple objects segmentation graph cut Gaussian mixture models

来源：评论

学校读者我要写书评

暂无评论

A geometric active contours model for multiple objects segmentation

引用

4th International Conference on Intelligent Computing

作者： He, Ning Zhang, Peng Lu, Ke Capital Normal Univ Sch Math Sci Beijing 100037 Peoples R China Grad Univ Chinese Acad Sci Coll Comp & Commun Engn Beijing 100049 Peoples R China

ISBN: (纸本)9783540874409

The technique of geometric active contours has become quite popular for a variety of applications, particularly image segmentation and classification problems. In traditional active contour models, snake initialization is performed manually by users, and topological changes, such as splitting of the snake, can not be automatically handled. In this paper, we present an automatic geometric active contours model which can extract multiple objects in an image without any manual assistance and completely eliminates the need of costly re-initialization procedure. The proposed framework is inspired by the geodesic active contour model and leads to a paradigm that is relatively free from the initial curve position. According to the proposed flow, the traditional boundary attraction term is replaced with a new force that guides the propagation to the object boundaries from both sides. This new geometric active contour model is implemented using a level set approach, thereby allowing dealing naturally with topological changes.

关键词： Geodesic active contour Level sets multiple objects segmentation

来源：评论

学校读者我要写书评

暂无评论

A Novel Approach for Automatic segmentation on multiple Starch Granules from Microscopic Images

A Novel Approach for Automatic Segmentation on Multiple Star...

引用

2011 World Congress on Engineering and Technology(CET 2011)

作者： Shengwen GUO a,* a Department of Biomedical Engineering, School of Electrical and Automation Engineering HeFei University of Technology, HeFei, P.R. China, 230009

Starch is the most important carbohydrate in the human diet and contained in many staple foods such as rice, wheat, corn, potatoes and cassava, etc. Currently, microscopic imaging technology is one of the most effective ways to investigate and analyze the structure of starches. segmentation of starch granules is a necessary step for starch granule structure analysis such as starch granules detection, shape recognition and size computation. This paper investigates a new method based on GVF (gradient vector flow) snake deformable model for starch granules segmentation. The proposed method focuses on full automatic segmentation on granules, especially on separation of adjacent starch granules, which occur widely in microscopic images. A novel energy function based on position and intensity is introduced into the directional gradient computation, thus the directional gradient is used to obtain the GVF snake, which drives the deforming contours to the real contours of multiple granules. We also discuss the splitting scheme for multiple GVF snakes during deformation process. Experimental results on synthetic and real images demonstrate its good performance in multiple starch granules segmentation.

关键词： starch microscopic imaging GVF snake effective energy multiple objects segmentation

来源：评论

学校读者我要写书评

暂无评论

Fast interactive segmentation algorithm of image sequences based on relative fuzzy connectedness

引用

Journal of Systems Engineering and Electronics 2005年第4期16卷 750-755页

作者： Tian Chunna Gao Xinbo School of Electronic Engineering Xidian Univ. Xi'an 710071 P. R. China

A fast interactive segmentation algorithm of image-sequences based on relative fuzzy connectedness is presented. In comparison with the original algorithm, the proposed one, with the same accuracy, accelerates the segmentation speed by three times for single image. Meanwhile, this fast segmentation algorithm is extended from single object to multiple objects and from single-image to image-sequences. Thus the segmentation of multiple objects from complex hackground and batch segmentation of image-sequences can be achieved. In addition, a post-processing scheme is incorporated in this algorithm, which extracts smooth edge with one-pixel-width for each segmented object. The experimental results illustrate that the proposed algorithm can obtain the object regions of interest from medical image or image-sequences as well as man-made images quickly and reliably with only a little interaction.

关键词： fuzzy connectedness interactive image segmentation image-sequences segmentation multiple objects segmentation fast algorithm.

来源：评论

学校读者我要写书评

暂无评论

Fast interactive segmentation algorithm of image sequences based on relative fuzzy connectedness

引用

Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology 2005年第10期27卷 1549-1554页

作者： Tian, Chun-Na Gao, Xin-Bo Halidan, A. School of Electronic Engineering Xidian University Xi'an 710071 China School of Electrical Engineering Xinjiang University Urumqi 830008 China

A fast interactive segmentation algorithm of image-sequences based on relative fuzzy connectedness is presented. In comparison with the existing algorithm, the proposed one, with the same accuracy, accelerates the segmentation speed by three times for single image. Meanwhile, this fast segmentation algorithm is extended from single object to multiple objects and from single-image to image-sequences. Thus the segmentation of multiple objects from complex background and batch segmentation of image-sequences can be achieved. In addition, a post-processing scheme is incorporated in this algorithm, which extracts smooth edge with one-pixel-width for each segmented object. The experimental results illustrate that the proposed algorithm can obtain the object regions of interest from medical image or image-sequences as well as man-made images quickly and reliably with only a little interaction.

关键词： Fuzzy connectedness Image-sequences segmentation Interactive image segmentation multiple objects segmentation

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：