首页    期刊浏览 2024年07月09日 星期二
登录注册

文章基本信息

  • 标题:Efficient Image Retrieval through Hybrid Feature Set and Neural Network
  • 本地全文:下载
  • 作者:Nitin Arora ; Alaknanda Ashok ; Shamik Tiwari
  • 期刊名称:International Journal of Image, Graphics and Signal Processing
  • 印刷版ISSN:2074-9074
  • 电子版ISSN:2074-9082
  • 出版年度:2019
  • 卷号:11
  • 期号:1
  • 页码:44-53
  • DOI:10.5815/ijigsp.2019.01.05
  • 出版社:MECS Publisher
  • 摘要:Images are an important part of daily life. Any person cannot easily control the huge repository of digitally existing images. Extensive scanning of the image database is very much essential to search a particular image from the huge repository. In some cases, this procedure becomes very exhaustive also. As a result, if a count of ten thousand, lakhs or considerably more images are included in the image database, then it may be transformed into a tedious and never-ending process. Content-based image retrieval (CBIR) is a technique, which is used for retrieving an image. This type of image retrieval procedure is centered on the real content of the image. This paper proposed a model of the hybrid feature set of Haar wavelets and Gabor features and analyzed with different existing models image retrieval. Content-based image retrieval using hybrid feature set of Haar wavelets and Gabor features superiors on other models.
  • 关键词:Content-based Image Retrieval;Information Retrieval;Color features;Texture features;Shape features
国家哲学社会科学文献中心版权所有