Image Classification and Annotation Based on Hadoop Cloud Computing Platform

Jiyuan Lu; Chenghui Huang; Fang Hou; Bin Li

doi:10.3969/j.issn.1000-0801.2014.02.008

您当前的位置：

首页 >

文章列表页 >

Image Classification and Annotation Based on Hadoop Cloud Computing Platform

research and development | 更新时间：2024-06-05

- Image Classification and Annotation Based on Hadoop Cloud Computing Platform
- Telecommunication Science Vol. 30, Issue 2, Pages: 65-69(2014)
- 作者机构：
  
  1. 广东金融学院计算机科学与技术系广州 510521
  2. 甲骨文研究开发中心（深圳）有限公司深圳 518057
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1000-0801.2014.02.008
  CLC：
- Published Online：2014-02，
  
  Published：20 February 2014
- 稿件说明：
移动端阅览
Jiyuan Lu, Chenghui Huang, Fang Hou, et al. Image Classification and Annotation Based on Hadoop Cloud Computing Platform[J]. Telecommunication science, 2014, 30(2): 65-69.
DOI：

Jiyuan Lu, Chenghui Huang, Fang Hou, et al. Image Classification and Annotation Based on Hadoop Cloud Computing Platform[J]. Telecommunication science, 2014, 30(2): 65-69. DOI： 10.3969/j.issn.1000-0801.2014.02.008.

摘要

为有效处理并利用互联网海量的图像和视频数据，提出了一种基于Hadoop云平台的图像分类和标注解决方案。针对如何高效地进行训练集提取这一重要问题，搭建了基于云计算的图像抓取平台，利用互联网的图像资源作为原始数据集，为提取训练集图像提供足够的数据；实现了基于概率潜在语义分析模型的训练集图像提取功能，对原始数据集进行基于主题的聚类，帮助用户快速选取训练集图像；加入了SVM分类模型，利用提取出来的训练集对未标注图像进行分类标注，实现了完整的系统。实验结果表明，该方案能够满足海量图像数据分类和标注的功能和性能需求。

Abstract

In order to effectively deal with the massive image and video data in internet，a solution for image classification and annotation based on Hadoop cloud platform was proposed.Firstly，a system based on cloud computing was given to crawl the raw data image from WWW.Secondly，a training image extractor based on pLSA （probabilistic latent semantic analysis）was presented to help users to get training set images effectively.Thirdly，the SVM model for the system was integrated，which could be used to classify or annotate novel images.According to the experiment，the system can both meet the functional requirement and achieve optimized performance for image data classification and annotation.

关键词

Keywords

references

Moosmann F ， Nowak E ， Jurie F . Randomized clustering forests for image classification . IEEE Transactions on Pattern Analysis and Machine Intelligence ， 2008 ， 30 （ 9 ）： 1632 ～ 1646

ALIPR . Automatic photo tagging and visual image search . http://www.alipr.com/ http://www.alipr.com/ ， 2012

GazoPa . Similar image search . http://www.gazopa.com/ http://www.gazopa.com/ ， 2010

Cai D ， He X F ， Ma W Y ， et al . Organizing www images based on the analysis of page layout and web link structure . Proceedings of 2004 IEEE International Conference on Multimedia and Expo，ICME’04 ， Sorrento，Italy ， 2004

Grangier D ， Bengio S . A discriminative kernel-based approach to rank images from text queries . IEEE Transactions on Pattern Analysis and Machine Intelligence ， 2008 ， 30 （ 8 ）： 1371 ～ 1384

Griffin G ， Holub A ， Perona P . Caltech-256 Object Category Dataset . Technical Report，California Institute of Technology ， 2007

Views

501

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Technical evolution and development trend of quantum computing cloud platform

Damage toughness assessment method of power backbone communication network based on power big data

Virtual machine scheduling model based on Shapley value modified genetic algorithm in cloud computing

Development status and trend prospect of computing power infrastructure

Time-frequency image and high-order spectrum characteristics based radar signal recognition

Related Author

HAO Yuanchen

XIE Yuheng

TANG Jianjun

Xue HAN

Kun MA

Lingyu XU

Xiaoping SHEN

Zhicheng GONG

Related Institution

Research Institute of China Telecom Co., Ltd.

Jiaxing Key Laboratory of Industrial Internet Security

Jiaxing Branch of China Telecom Co., Ltd.

Jiaxing Nanyang Polytechnic Institute

Jiaxing Vocational Technical College

⁰