检索结果-内蒙古大学图书馆

Object information based interactive segmentation for fatty tissue extraction

COMPUTERS IN BIOLOGY AND MEDICINE 2013年第10期43卷 1462-1470页

作者： Zhou, Zhi-Guo Liu, Fang Jiao, Li-Cheng Li, Ling-Ling Wang, Xiao-Dong Gou, Shui-Ping Wang, Shuang Xidian Univ Sch Comp Sci & Technol Xian 710071 Peoples R China Xidian Univ Minist Educ China Key Lab Intelligent Percept & Image Understanding Xian 710071 Peoples R China

Lymph nodes are very important factors for diagnosing gastric cancer in clinical use, and are usually distributed within the fatty tissue around the stomach. When extracting fatty tissues whose structures and textures are complicated, automatic extraction is still a challenging task, while manual extraction is time-consuming. Consequently, semi-automatic extraction, which allows introducing interactive operations, appears to be more realistic. Currently, most interactive methods need to indicate the position and main features in both the object and background. However, it is easier for radiologists to only mark object information. Due to this issue, a new Object Information based interactive segmentation (OHS) method is proposed in this paper. Different from the most existing methods, OIIS just needs to input the object information, while the background information is not required. Experimental results and comparative studies show that OIIS is effective for fatty tissue extraction. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Fatty tissue Gastric cancer interactive image segmentation Object information Mean shift

来源：评论

学校读者我要写书评

暂无评论

interactive object segmentation from multi-view images

引用

JOURNAL OF VISUAL COMMUNICATION AND image REPRESENTATION 2013年第4期24卷 477-485页

作者： Thi Nhat Anh Nguyen Cai, Jianfei Zheng, Jianmin Li, Jianguo Danang Univ Technol Da Nang City Vietnam Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore

Despite the great progress on interactive image segmentation, image co-segmentation, 2D and 3D segmentation, there is still no workable solution to the problem: given a set of calibrated or un-calibrated multi-view images (say, more than 40 images), by interactively cutting 3 similar to 4 images, can the foreground object of the rest images be quickly cutout automatically and accurately? In this paper, we propose a non-trivial engineering solution to this problem. Our basic idea is to integrate 3D segmentation with 2D segmentation so as to combine their advantages. Our proposed system iteratively performs 2D and 3D segmentation, where the 3D segmentation results are used to initialize 2D segmentation and ensure the silhouette consistency among different views and the 2D segmentation results are used to provide more accurate cues for the 3D segmentation. The experimental results show that the proposed system is able to generate highly accurate segmentation results, even for some challenging real-world multi-view image sequences, with a small amount of user input. (c) 2013 Elsevier Inc. All rights reserved.

关键词： interactive image segmentation Multi-view image segmentation image co-segmentation image segmentation 3D graph-cut Active contour Object cutout Joint 3D and 2D segmentation

来源：评论

学校读者我要写书评

暂无评论

An automatic geo-spatial object recognition algorithm for high resolution satellite images

An automatic geo-spatial object recognition algorithm for hi...

引用

Conference on Electro-Optical Remote Sensing, Photonic Technologies, and Applications VII;and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing

作者： Ergul, Mustafa Alatan, A. Aydin METU Elect & Elect Engn Dept TR-06531 Ankara Turkey

ISBN: (纸本)9780819497666

This paper proposes a novel automatic geo-spatial object recognition algorithm for high resolution satellite imaging. The proposed algorithm consists of two main steps;a hypothesis generation step with a local feature-based algorithm and a verification step with a shape-based approach. In the hypothesis generation step, a set of hypothesis for possible object locations is generated, aiming lower missed detections and higher false-positives by using a Bag of Visual Words type approach. In the verification step, the foreground objects are first extracted by a semi-supervised image segmentation algorithm, utilizing detection results from the previous step, and then, the shape descriptors for segmented objects are utilized to prune out the false positives. Based on simulation results, it can be argued that the proposed algorithm achieves both high precision and high recall rates as a result of taking advantage of both the local feature-based and the shape-based object detection approaches. The superiority of the proposed method is due to the ability of minimization of false alarm rate and since most of the object shapes contain more characteristic and discriminative information about their identity and functionality.

关键词： Object recognition interactive image segmentation shape descriptors foreground extraction

来源：评论

学校读者我要写书评

暂无评论

Haptic image Exploration

Haptic Image Exploration

引用

作者： Lareau, David Uottawa

学位级别：master

The haptic exploration of 2-D images is a challenging problem in computer haptics. Research on the topic has primarily been focused on the exploration of maps and curves. This thesis describes the design and implementation of a system for the haptic exploration of photographs. The system builds on various research directions related to assistive technology, computer haptics, and image segmentation. An object-level segmentation hierarchy is generated from the source photograph to be rendered haptically as a contour image at multiple levels-of-detail. A tool for the authoring of object-level hierarchies was developed, as well as an innovative type of user interaction by region selection for accurate and efficient image segmentation. According to an objective benchmark measuring how the new method compares with other interactive image segmentation algorithms shows that our region selection interaction is a viable alternative to marker-based interaction. The hierarchy authoring tool combined with precise algorithms for image segmentation can build contour images of the quality necessary for the images to be understood by touch with our system. The system was evaluated with a user study of 24 sighted participants divided in different groups. The first part of the study had participants explore images using haptics and answer questions about them. The second part of the study asked the participants to identify images visually after haptic exploration. Results show that using a segmentation hierarchy supporting multiple levels-of-detail of the same image is beneficial to haptic exploration. As the system gains maturity, it is our goal to make it available to blind users

关键词： Haptics interactive image segmentation image Exploration Human Computer Interaction Hierarchical segmentation Assistive Technology

来源：评论

学校读者我要写书评

暂无评论

Separability-based intelligent scissors for interactive image segmentation

引用

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2007年第1期E90D卷 137-144页

作者： Suetake, Noriaki Uchino, Eiji Hirata, Kanae Yamaguchi Univ Fac Sci Dept Phys Biol & Informat Yamaguchi 7538512 Japan FLSI Iizuka Fukuoka 8200067 Japan

Intelligent scissors is an interactive image segmentation algorithm which allows a user to select piece-wise globally optimal contour segment corresponding to a desired object boundary. However, the intelligent scissors is too sensitive to a noise and texture patterns in an image since it utilizes the gradient information concerning the pixel intensities. This paper describes a new intelligent scissors based on the concept of the separability in order to improve the object boundary extraction performance. The effectiveness of the proposed method has been confirmed by some experiments for actual images acquired by an ordinary digital camera.

关键词： interactive image segmentation intelligent scissors separability magic wand active contour model

来源：评论

学校读者我要写书评

暂无评论

image Foresting Transform: On-the-Fly Computation of segmentation Boundaries 1

引用

17th Scandinavian Conference on image Analysis (SCIA)

作者： Malmberg, Filip Uppsala Univ Ctr Image Anal Uppsala Sweden

ISBN: (数字)9783642212277

ISBN: (纸本)9783642212277

The image Foresting Transform (IFT) is a framework for seeded image segmentation, based on the computation of minimal cost paths in a discrete representation of an image. In two recent publications, we have shown that the segmentations obtained by the IFT may be improved by refining the segmentation locally around the boundaries between segmented regions. Since these methods operate on a small subset of the image elements only, they may be implemented efficiently if the set of boundary elements is known. Here, we show that this set may be obtained on-the-fly, at virtually no additional cost, as a by-product of the IFT algorithm.

关键词： interactive image segmentation image Foresting Transform

来源：评论

学校读者我要写书评

暂无评论

LEARNING TO DETECT SALIENT REGION OF image UNDER WEAK SUPERVISION

LEARNING TO DETECT SALIENT REGION OF IMAGE UNDER WEAK SUPERV...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Cheng, Jian Fu, Yu Lu, Hanqing Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100864 Peoples R China

ISBN: (纸本)9781612843490

Salient region of an image usually contains the crucial information for image analysis and understanding. Most conventional approaches learn the saliency by utilizing the low-level features, which ignore the participation of human. In this pap er, we propose an effective and robust approach to detect the salient region of an image by combining the bottom-up and top-down cues. The proposed method not only consider the low-level attention features, but also take human into the loop for better understanding of human attention. Furthermore, we build an asymmetrical graph model to integrate these bottom up and top-down cues into an energy function of saliency. A compact but exact saliency region can be obtained by minimizing posterior energy function. The compact constraint and global minimization manner of the asymmetrical graph cuts guarantee the good performance of saliency extraction. Extensive experiments demonstrate the proposed method is promising.

关键词： Saliency detection interactive image segmentation graph cuts

来源：评论

学校读者我要写书评

暂无评论

An Improved Video Matting Technique Based on GrabCut

An Improved Video Matting Technique Based on GrabCut

引用

3rd International Conference on Digital image Processing (ICDIP 2011)

作者： Yang, Lei Ma, Chunxi Wu, Xiaoyu Li, Shaobin Wang, Xiaomeng Commun Univ China Digital Media Dept Beijing Peoples R China Commun Univ China Digital Media Dept Beijing Peoples R China Commun Univ China Televis Engn Dept Beijing Peoples R China Commun Univ China Radio & Televis Engn Dept Beijing Peoples R China

ISBN: (纸本)9780819485830

Now GrabCut algorithm is a comparatively ideal interactive image segmentation method, and it has the advantages of high precision segmentation and low interaction. But so far GrabCut operator is an interactive segmentation method only be used in static images. To solve this problem, this paper proposes a method of video matting, which is based on the GrabCut operator. This method is going to achieve video auto-mating by transmitting the matting result of a frame to the next frame. And this method improves the processing speed. By experiments, this method demonstrates a wonderful segmentation result.

关键词： GrabCut algorithm interactive image segmentation Matting technology

来源：评论

学校读者我要写书评

暂无评论

CONTENT-SENSITIVE COLLECTION SNAPPING

CONTENT-SENSITIVE COLLECTION SNAPPING

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Fu, Yanwei Guo, Yanwen Nanjing Univ Natl Key Lab Novel Software Technol Nanjing Peoples R China Nanjing Univ Jiangyin Informat Technol Res Inst Nanjing Peoples R China

ISBN: (纸本)9781612843490

interactive segmentation methods have greatly simplified the task of object cutout from an image. However, segmenting a large number of images in a collection is still a tedious task. In this paper, we present a content-sensitive group segmentation method that iteratively segments the images in a collection and incrementally refines the results. With our method, a user only provides a small number of strokes to segment and refine a few sample images. For each of the rest of images, our method finds relevant sample images and applies the corresponding appearance models to guide the segmentation. To improve the segmentation results using the user strokes on a few images with unsatisfactory segmentation results, our method calculates the relevance map that measures the probability that a stroke can be appropriately applied at each pixel/region of an image, and applies it accordingly. Our experiments show that our method can effectively segment an image collection with a wide variety of image content and significantly reduce user input.

关键词： interactive image segmentation Collection segmentation Cosegmentation

来源：评论

学校读者我要写书评

暂无评论

image segmentation algorithms based on the machine learning of features

引用

PATTERN RECOGNITION LETTERS 2010年第14期31卷 2325-2336页

作者： Lee, Sang Hak Koo, Hyung Il Cho, Nam Ik Seoul Natl Univ Sch Elect Engn Seoul South Korea

For general purpose image segmentation, it is required to find and integrate the features that best characterize the regions to be segmented. This paper proposes a machine learning approach to finding the appropriate features and also a new segmentation method based on the information obtained while learning. Precisely, our method is based on the AdaBoost algorithm for learning the difference between regions, and the CRF-based (conditional random fields) energy formulation for the segmentation using the information from the learning. We have applied our method to interactive (semi-automatic) and unsupervised (fully-automatic) segmentation problems. While the interactive case is relatively straightforward due to the nature of our machine learning scheme, the unsupervised case is not. Hence, for the unsupervised segmentation, we devise a new initialization method and an EM-like (Expectation-Maximization) optimization method that iterates AdaBoost learning and graph-cuts. The analysis shows that the number of regions is automatically determined so that only distinguishable regions are survived. Experimental results also show that the proposed method gives promising results in diverse applications such as texture segmentation, color-texture segmentation, and page segmentation. 2010 Elsevier B.V. All rights reserved.

关键词： image segmentation interactive image segmentation Unsupervised image segmentation AdaBoost image features

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：