Satellite Image Classification and Content-Base Image Retrieval Using Type-2 Fuzzy Logic
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 6
Abstract
Abstract: The detection of oceanic structures, such as upwelling’s or eddies, from satellite images has significance for marine environmental studies, coastal resource management, and ocean dynamics studies. There is a lack of tools that allow us to retrieve automatically relevant structures from large satellite image databases. This Paper focuses on the development and validation of a Content-Based Image Retrieval (CBIR) system to classify and retrieve oceanic structures from satellite images with improved accuracy. The image we obtain from http://oceancolor.gsfc.nasa.gov/, which give images from different satellite like Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), or MEdium Resolution Imaging Spectrometer (MERIS). During the processing of satellite images, different types of imperfection (uncertainties, ambiguities and vagueness) can occur. These imperfections can involve the gray‐level intensities, the geometrical characteristics and relations among image objects, and the expert knowledge itself used to overcome these problems. The CBIR system includes several types of soft computing technologies, such as neural networks and fuzzy logic. An advantage of fuzzy logic approach is that the system can be more comprehensible to human users because fuzzy databases (DBs) manage a terminology close to natural languages. This system give retrieval of most relevant and typical oceanic structures, such as upwelling, eddies and wakes.
Authors and Affiliations
Prof. Anita Thengade , Shirish A. Agale
Keywords
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