Brain Tumor Detection and Analysis using SVM and LVQ Classifier |
Author(s): |
| Aliaja Salauddin Jamadar , Maratha Mandal Engineering College, Belgaum, Karnataka, India; Vaibhav Kakade, Maratha Mandal Engineering College, Belgaum, Karnataka, India |
Keywords: |
| Tumor, Classifier, Local Binary Pattern (LBP), Support Vector Machine (SVM), Learning Vector Quantization (LVQ) |
Abstract |
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Brain tumor is an abnormal and uncontrolled growth of tissues in human brain. Brain tumor diagnosis is very complex task. In biomedical field image processing is strongly growing issue. Many techniques and approaches has been described for image processing. This paper provides more efficient method to detect and analyze brain tumor. Proposed system gives efficient and more accurate quantitative results. Here in this method the steps are preprocessing, anisotropic diffusion, feature extraction, classification. Classifications used are support vector machine (SVM) and Learning vector quantization (LVQ). Here we are comparing these two classification, we get the LVQ classification which is special case of neural network gives more accuracy than the SVM classification. |
Other Details |
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Paper ID: IJSRDV3I50545 Published in: Volume : 3, Issue : 5 Publication Date: 01/08/2015 Page(s): 754-757 |
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