Image retrieval based convolutional neural network
Joint Authors
Shakir, Shayma Hamid
Khassaf, Nuha Muhammad
Source
al-Mustansiriyah Journal of Science
Issue
Vol. 31, Issue 4 (31 Dec. 2020), pp.43-54, 12 p.
Publisher
al-Mustansyriah University College of Science
Publication Date
2020-12-31
Country of Publication
Iraq
No. of Pages
12
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
At the present time, everyone is interested in dealing with images in different fields such as geographic maps, medical images, images obtaining by Camera, microscope, telescope, agricultural field photos, paintings, industrial parts drawings, space photos, etc.
Content Based Image Retrieval (CBIR) is an efficient retrieval of relevant images from databases based on features extracted from the image.
Follow the proposed system for retrieving images related to a query image from a large set of images, based approach to extract the texture features present in the image using statistical methods (PCA, MAD, GLCM, and Fusion) after pre-processing of images.
The proposed system was trained using 1D CNN using a dataset Corel10k which widely used for experimental evaluation of CBIR performance the results of proposed systemshows that the highest accuracy is 97.5% using Fusion (PCA, MAD), where the accuracy is 95% using MAD, 90% using PCA.
The performance result is acceptable compared to previous work.
American Psychological Association (APA)
Khassaf, Nuha Muhammad& Shakir, Shayma Hamid. 2020. Image retrieval based convolutional neural network. al-Mustansiriyah Journal of Science،Vol. 31, no. 4, pp.43-54.
https://search.emarefa.net/detail/BIM-1268838
Modern Language Association (MLA)
Khassaf, Nuha Muhammad& Shakir, Shayma Hamid. Image retrieval based convolutional neural network. al-Mustansiriyah Journal of Science Vol. 31, no. 4 (2020), pp.43-54.
https://search.emarefa.net/detail/BIM-1268838
American Medical Association (AMA)
Khassaf, Nuha Muhammad& Shakir, Shayma Hamid. Image retrieval based convolutional neural network. al-Mustansiriyah Journal of Science. 2020. Vol. 31, no. 4, pp.43-54.
https://search.emarefa.net/detail/BIM-1268838
Data Type
Journal Articles
Language
English
Notes
-
Record ID
BIM-1268838