Cited by 257Image Retrieval and Classification TechniquesFace and Expression RecognitionComputer Science and Engineering

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Feature Extraction Methods: A Review

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Mutlag, Wamidh K., Ali, Shaker K., Aydam, Zahoor M., Taher, Bahaa H.·2020·Journal of Physics: Conference Series

DOI 10.1088/1742-6596/1591/1/012028

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Abstract

Feature extraction is the main core in diagnosis, classification, clustering, recognition, and detection. Many researchers may by interesting in choosing suitable features that used in the applications. In this paper, the most important features methods are collected, and explained each one. The features in this paper are divided into four groups; Geometric features, Statistical features, Texture features, and Color features. It explains the methodology of each method, its equations, and application. In this paper, we made acomparison among them by using two types of image, one type for face images (163 images divided into 113 for training and 50 for testing) and the other for plant images(130 images divided into 100 for training and 30 for testing) to test the features in geometric and textures. Each type of image group shows that each type of images may be used suitable features may differ from other types.

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Authors: Mutlag, W. K., Ali, S. K., Aydam, Z. M., & Taher, B. H.
Affiliations: Southern Technical University (IQ)
Thi Qar University (IQ)
University of Sumer (IQ)
Corresponding author: Ali, Shaker K.
Aydam, Zahoor M.
ORCID: Mutlag, Wamidh K.
Ali, Shaker K.
Aydam, Zahoor M.
Taher, Bahaa H.
Venue: Journal of Physics: Conference Series
Publisher: IOP Publishing
Published: 2020-07-01
Volume: 1591
Issue: 1
Pages: 012028
ISSN: 1742-6588 (ISSN-L)
1742-6596
DOI: 10.1088/1742-6596/1591/1/012028
OpenAlex: W3049180962
Cited by: 257
References: 11
Citations by year: 2026: 32 · 2025: 72 · 2024: 71 · 2023: 46 · 2022: 25 · 2021: 11
FWCI: 6.32
Type: conference paper
Language: en
Open access: diamond
doi.org
Licence: cc-by
creativecommons.org/licenses/by/3.0/ (vor)
iopscience.iop.org/info/page/text-and-data-mining (tdm)
Locations: Journal of Physics Conference Series (publishedVersion, cc-by)
Topics: Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
Physical Sciences › Computer Science › Artificial Intelligence › Computer Science and Engineering
Keywords: feature extraction, geometric features, statistical features, texture features, color features, face images, plant images, feature comparison, image classification

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