期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：1
DOI：10.15680/ijircce.2015.0301062
出版社：S&S Publications
摘要：Content-based image retrieval system has been an active research topic in areas such as, entertainment,multimedia, education, image classification and searching. One of the key issues with the Content-based imageretrieval system is to extract essential information from the raw data which reflect the image content. Even though largenumbers of feature extraction and retrieval techniques have been developed, there are still no globally acceptedtechniques available for region/object representation and retrieval. In this paper, we propose an Adaptive neuro fuzzyinference system (ANFIS), it has a potential to capture both benefits of neutral network and fuzzy logic. The Colorextraction is done based on RGB (red, green, blue), HSV (hue, saturation value) and Y,Cb,Cr (luminance andchrominance).Texture of an image is extracted by Gray Level Co-Occurrence Matrix (GLCM) which is a popularstatistical method. Shape extraction of an image can be determined by Canny Edge Detection. Thus the experimentalresults may show that our retrieval framework is very effective and requires less computation time with an uniquesystemic processes and outperforms the conventional image retrieval systems. The experiment results are analyzedbased on the Corel Datasets.
