Otsu and Mathematical Morphology for Breast Cancer Classification
ASM Science Journal · 2020
Segmentation is one of the essential components in Computer Aided Diagnosis (CADx).This paper proposed a combination of Otsu and mathematical morphology for segmentation phase in classifying breast cancer.Then, the features of the segmented images will be extracted by using Speed Up Robust Features (SURF).Finally, the corresponding features will be classified using several classifiers.It is found that the Support Vector Machine (SVM) classifier shows the highest accuracy rate among other classifiers.Moreover, experimental results show that the proposed combination method shows promising results.