Enhancement of principal component analysis using Gaussian blur filter
Other Title(s)
تحسين تحليل المكون الرئيسي باستخدام منقي التمويه للشي الضبابي
Joint Authors
Ali, Yusra Husayn
Midhat, Rim Aqil
Source
Issue
Vol. 59, Issue 3B (30 Sep. 2018), pp.1509-1517, 9 p.
Publisher
University of Baghdad College of Science
Publication Date
2018-09-30
Country of Publication
Iraq
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
Characteristic evolving is most serious move that deal with image discrimination.
It makes the content of images as ideal as possible.
Gaussian blur filter used to eliminate noise and add purity to images.
Principal component analysis algorithm is a straightforward and active method to evolve feature vector and to minimize the dimensionality of data set, this paper proposed using the Gaussian blur filter to eliminate noise of images and improve the PCA for feature extraction.
The traditional PCA result as total average of recall and precision are (93% ,97%) and for the improved PCA average recall and precision are (98% ,100%), this show that the improved PCA is more effective in recall and precision.
American Psychological Association (APA)
Ali, Yusra Husayn& Midhat, Rim Aqil. 2018. Enhancement of principal component analysis using Gaussian blur filter. Iraqi Journal of Science،Vol. 59, no. 3B, pp.1509-1517.
https://search.emarefa.net/detail/BIM-875838
Modern Language Association (MLA)
Ali, Yusra Husayn& Midhat, Rim Aqil. Enhancement of principal component analysis using Gaussian blur filter. Iraqi Journal of Science Vol. 59, no. 3B (2018), pp.1509-1517.
https://search.emarefa.net/detail/BIM-875838
American Medical Association (AMA)
Ali, Yusra Husayn& Midhat, Rim Aqil. Enhancement of principal component analysis using Gaussian blur filter. Iraqi Journal of Science. 2018. Vol. 59, no. 3B, pp.1509-1517.
https://search.emarefa.net/detail/BIM-875838
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 1517
Record ID
BIM-875838