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Vol.11, No.3, August 2022. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
Fusion of Hand-crafted and Deep Features for Automatic Diabetic Foot Ulcer Classification
Nora Al-Garaawi, Zainab Harbi, Tim Morris
© 2022 Nora Al‐Garaawi, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 11, Issue 3, Pages 1055-1064, ISSN 2217-8309, DOI: 10.18421/TEM113-10, August 2022.
Received: 08 March 2022. Revised: 12 June 2022.
Abstract:
This paper proposes to combine both the texture and deep features to build a robust diabetic foot ulcer recognition system since both features represent valuable information about the disease. The proposed system consists of three stages: feature extraction, feature fusion, and DFU classification. The feature extraction is performed by extracting the handcrafted and deep features. The feature fusion is performed by concatenating both feature vectors into a single vector. The DFU classification is performed by training a random forest classifier on the fusion vectors and the resulting classifier is used then for classification. Experimental results showed that the proposed approach provides satisfactory performance in DFU, ischaemia, and infection classification.
Keywords –diabetic foot ulcer, classification, ischaemia and infection, hand-crafted features, deep features, fusion features. |
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