Gray Level Cooccurrence Matrix Feature Extraction and Fuzzy Based Discriminative Binary Descriptor for Medical Image Retrieval - Renukadevi, NT; Karunakaran, S; Saraswathi, K (International Journal of Computer Sciences and Engineering, 2019)
Medical image retrieval plays an more important role in the medical research environment which needs to done fastly and accurately for improved performance. In our previous research method it is done by introducing coiflets wavelet based feature extraction and SVM based classification. However this research method cannot perform well with the presence of increased noise level and the minuter feature information. This is resolved in this research method by introducing method namely Gray Level Co occurrence Matrix Feature Extraction and Fuzzy Based Discriminative Binary Descriptor (GLCMFE-FBDBD). It contains five major steps such as deblurring, preprocessing, feature extraction, detection of most discriminative bin and subspace clustering. In this research method, the image deblurring is accomplished by utilizing Artificial Bee Colony (ABC) algorithm. Preprocessing is done by using min-max normalization; feature extraction is done by using gray level concurrence matrix Then FSK Function is used to discover the most discriminative bin selection. SC is presented for quick image retrieval. The MRI brain tumor images are used for evaluation. Finally, the results show that the proposed work gives greater performance compared to the previous work.