ANFIM: Adaptive Neuro Fuzzy Inference Model For Content Based Image Retrieval

摘要

Content based image retrieval, in the last few years has received a wide attention due to the development of multimedia technology. Nevertheless, it remains a challenging task due to the retrieval of images in an efficient time by means of classification process. This paper focuses on the development and validation of a content-based image retrieval system to classify and retrieve images using adaptive neuro fuzzy inference system. The proposed system consist of the following phases (i) Preprocessing of input images using Contrast-Limited Adaptive Histogram Equalization (CLAHE), (ii) Extraction of features using Gray Level Co-Occurrence Matrix (GLCM), (iii) Classification of images are performed using Adaptive neuro fuzzy inference model (ANFIM).The Experimental results show that the proposed retrieval framework is very effective and requires less computation time when compared with the state-of-art retrieval systems, and results in 94.6% of prediction accuracy.