Content-Based Image Retrieval Using Customized Convolutional Neural Network

被引：0
|
作者：
Nilawar, A. P. [1 ]
Dethe, C. G. [2 ]
Jaiswal, A. [1 ]
Kene, J. D. [1 ]
机构：
[1] Shri Ramdeobaba Coll Engn & Management, Dept Elect & Commun Engn, Nagpur, Maharashtra, India
[2] RTMNU, UGC HRDC, Nagpur, Maharashtra, India
来源：
BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS | 2020年 / 13卷 / 14期
关键词：
CONTENT-BASED IMAGE RETRIEVAL; CNN; DNN; LSH;
D O I：
10.21786/bbrc/13.14/105
中图分类号：
Q81 [生物工程学（生物技术）]; Q93 [微生物学];
学科分类号：
071005 ; 0836 ; 090102 ; 100705 ;
摘要：
In today's world due to multimedia development, there is a huge image database. Content-Based Image retrieval (CBIR) is a widely used method for image retrieval from a large image database. Existing retrieval methods are based on the basic content of an image like color, Shape, and Texture. The system based on basic features requires more time for processing and provides less accuracy. To reduce time and improve accuracy we are proposing CBIR Using CNN in this paper. CNN is used for feature extraction and similarity measurement Hamming distance is used. In this technique, the user has to provide an image as an input query image. The similar images related to the query image are displayed as a result. The performances of a system are evaluated by precision and mean average precision (MAP). After comparing with existing methods, we found encouraging results that lead to improving accuracy.
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页码：467 / 470
页数：4
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