• Rakshavi Dessai
• Ganesh V. Manerkar

A brain tumor is an abnormal development of cells within the brain. MRI images are best appropriate for brain tumor detection. Otsu Binarization thresholding method is used to convert the grayscale images into binary images. K-means clustering is used to detect the tumor area from MRI images. Discrete Wavelet Transform(DWT), Gray Level Co-occurrence Matrix(GLCM) and Principal Component Analysis(PCA) are applied for feature extraction, feature reduction respectively. The extracted features are used for classifying low-grade glioma and high-grade glioma using the SVM classifier. The proposed work is to classify low-grade glioma images into grade 1, grade 2 images and high-grade glioma images into grade 3 and grade 4 images.

"An Enhanced Brain Tumor Detection and Classification Mechanism using Hybrid SVM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.147-151, June 2019, Available :http://www.jetir.org/papers/JETIR1906O23.pdf

"An Enhanced Brain Tumor Detection and Classification Mechanism using Hybrid SVM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp147-151, June 2019, Available at : http://www.jetir.org/papers/JETIR1906O23.pdf