Classification of Chronic Obstructive Pulmonary Disease (COPD) using Gabor Filter With SVM Classifier
V.Porkodi1, S. Anbu Karuppusamy2
1V.Porkodi*, Research Scholar, Department of Computer Science and Engineering, Shri Venkateshwara University, Gajraula, Amroha, (Uttar Pradesh), India.
2Dr. S. Anbu Karuppusamy, Professor, Department of Electronics and Communication Engineering, Excel Engineering College, Namakkal, (Tamil Nadu), India.
Manuscript received on September 17, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 787-790 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1392109119/2019©BEIESP | DOI: 10.35940/ijeat.A1392.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the field of medical diagnosis, early detection of COPD symptoms is difficult. The use of predictive tests leads to the treatment of COPD and also helps to identify signs of COPD early. Therefore, we present in this paper a feature extraction method for the structural representation of COPD images using the Gabor Filter. In addition, we train and evaluate COPD extracted function or category with SVM classification. The results show that the proposed method can be more accurate, more flexible, and more reliable. This approach is well adapted for early diagnosis of COPD.
Keywords: COPD Abnormalities, Classification, Gabor filter, SVM Classifier.