检索结果-内蒙古大学图书馆

Image retrieval based on ASIFT features in a Hadoop clustered system

IET IMAGE PROCESSING 2020年第1期14卷 138-146页

作者： Huang, Yin-Fu Wu, Huan-Yu Natl Yunlin Univ Sci & Technol Dept Comp Sci & Informat Engn 123 Univ RdSect 3 Touliu 640 Yunlin Taiwan

For image matching, the scale invariant feature transform (SIFT) algorithm is a commonly used one. They are invariant to image rotation, scale zooming, and partially invariant to change in illumination and 3D camera viewpoint. Affine SIFT (ASIFT) is an extension of SIFT, which solves the problem when images are captured at different angles. However, ASIFT has higher computational complexity than SIFT, due to a huge amount of features in the images. Therefore, in this study, a Hadoop-based image retrieval system is proposed to solve the ASIFT shortcomings of high computation by the MapReduce technology. The system uses a combination of the Bag-of-Words method and support vector machine. Finally, the experimental results verify that the proposed method is more effective than the other state-of-the-art methods for a variety of datasets.

关键词： image matching affine transforms parallel processing feature extraction support vector machines computational complexity image retrieval stereo image processing ASIFT features image matching scale invariant feature transform algorithm image rotation scale zooming 3D camera viewpoint affine SIFT higher computational complexity Hadoop-based image retrieval system Hadoop clustered system MapReduce technology bag-of-words method support vector machine

来源：评论

学校读者我要写书评

暂无评论

Content Based Image Retrieval using Local and Global features descriptor 2

Content Based Image Retrieval using Local and Global feature...

引用

2nd International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Kabbai, Leila Abdellaoui, Mehrez Douik, Ali Univ Monastir Natl Engn Sch Monastir Tunisia Univ kairouan Higher Inst Appl Sci & Technol Kairouan Kairouan Tunisia Univ Sousse Natl Engn Sch Sousse Tunisia

ISBN: (纸本)9781467385268

Recently, Content Based Image Retrieval (CBIR) has received a great attention by researchers. It becomes one of the most interesting topic in computer vision and image processing. CBIR image can be represent by local or global features. The entire image is described in the case of global features by using a novel descriptor called Upper-Lower of Local Binary Pattern (UL-LBP) based on Local Binary Pattern (LBP). Whereas, local features extract the Interest Points (IP) using scale invariant feature transform algorithm (SIFT). These features take into account the color channels information (Red, Green and Blue) independently in order to enhance results. This paper presents a hybrid approach for CBIR which combines both local and global feature of an image to generate a new descriptor denoted Histogram of Local and Global features using SIFT (HLG-SIFT). The performance of our descriptor is evaluated by computing the precision and recall using Euclidean distance and compared to state of the art.

关键词： scale invariant feature transform algorithm Local Binary Pattern Image Retrieval

来源：评论

学校读者我要写书评

暂无评论

Remote Sensing Image Registration Using SIFT and Vegetation Index Analysis

Remote Sensing Image Registration Using SIFT and Vegetation ...

引用

International Congress on Image and Signal Processing

作者： Buyun Lv Liaoying Zhao Xiaorun Li Inst. of Comput. Applic. Hangzhou Dianzi Univ. Hangzhou China

ISBN: (纸本)9781479958368

Aiming at the high accuracy and speed requirements of images registration for multiband data or hyperspectral data, a new method which combines scale invariant feature transform (SIFT) with vegetation index analysis is put forward. Firstly, feature points extracted by SIFT algorithm are classified into two sets -points on vegetation area and points on non-vegetation area, which is based on vegetation index;then the two sets of feature points are matched separately using spectral angle distance as the similarity measure. transformation parameters are obtained by least square method after mismatched points are removed. Experimental results show that the proposed method achieves higher speed as well as good registration accuracy.

关键词： geophysical image processing hyperspectral imaging image matching image registration least squares approximations vegetation vegetation mapping feature points hyperspectral data least square method multiband data nonvegetation area remote sensing image registration accuracy scale invariant feature transform algorithm similarity measure spectral angle distance transformation parameters vegetation index analysis Accuracy algorithm design and analysis feature extraction Image registration Indexes Remote sensing Vegetation mapping SIFT algorithm vegetation index

来源：评论

学校读者我要写书评

暂无评论

1.15mW Mixed-mode Neuro-Fuzzy Accelerator for Keypoint Localization in Image Processing

1.15mW Mixed-mode Neuro-Fuzzy Accelerator for Keypoint Local...

引用

54th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Hong, Injoon Oh, Jinwook Yoo, Hoi-Jun Korea Adv Inst Sci & Technol Dept Elect Engn Taejon 305701 South Korea

ISBN: (纸本)9781612848570

A mixed-mode neuro-fuzzy accelerator is proposed for keypoint localization of image features of scale invariant feature transform (SIFT) algorithm. To reduce processing time of keypoint localization with low power consumption, analog Adaptive Neuro-Fuzzy Inference System (ANFIS) and digital controller are implemented together. It is implemented in 0.13 mu m CMOS process and achieves 1.15mW power consumption. Compared to the conventional digital standalone system, 0.733mm(2) neuro-fuzzy accelerator achieves 43% processing time reduction and also results in 19.4% time reduction of image feature extraction process.

关键词： CMOS process Noise measurement Process control analog adaptive neuro-fuzzy inference system digital controller digital standalone system feature extraction fuzzy neural nets image feature extraction process image processing keypoint localization low power consumption mixed-mode neuro-fuzzy accelerator power 1.15 mW scale invariant feature transform algorithm transforms

来源：评论

学校读者我要写书评

暂无评论

Video image mosaics in real-time based on SIFT

Video image mosaics in real-time based on SIFT

引用

International Conference on Pervasive Computing, Signal Processing and Applications

作者： Ping, Yang Zheng, Mao Anjie, Gao Feng, Qi School of Electronic Information and Control Engineering Beijing University of Technology Beijing China

ISBN: (纸本)9780769541808

This paper proposes the method of video image mosaics in real-time based on scale invariant feature transform (SIFT) algorithm. The real-time processing is great significant for the video image mosaics. SIFT is the efficient method for extracting distinctive invariant features from images. But it costs so much computation time that it can't meet the real-time processing demand. Therefore, an improved SIFT approach is proposed in this paper to accelerate its execution. The result shows that the method is validated and meets the real-time processing computation demand. © 2010 IEEE.

关键词： SIFT feature extraction feature extraction image matching image segmentation real time processing computation demand scale invariance scale invariant feature transform algorithm transforms video image mosaics video image mosaics video signal processing

来源：评论

学校读者我要写书评

暂无评论

The Method of Pavement Image Splicing Based on SIFT algorithm

The Method of Pavement Image Splicing Based on SIFT Algorith...

引用

1st WRI Global Congress on Intelligent Systems (GCIS 2009)

作者： Hou Xiang-dan Dong Yong-feng Guo Hai-jiao Yang Xin Hebei Univ Technol Coll Comp Sci & Software Tianjin 300401 Peoples R China

ISBN: (纸本)9780769535715

According to the characteristic of pavement image, a new splicing method for pavement image based on scale invariant feature transform was proposed The SIFT algorithm is used to detect the feature points, FCM clustering is used to find the most similitude cluster relative to the number of feature point, and match the feature descriptors in the cluster, then the false feature points pair is rejected v RANSAC algorithm. Finally the correct match feature point's pair is used to realize image splicing in order to display the panoramic images of pavement images. There is a great reference value for improving the system of pavement image Automatic defection.

关键词： image splicing scale invariant feature transform algorithm FCM clustering eliminate mismatch

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：