标题：Using Wavelet and Fast Discrete Curvelet Transform (FDCT) with (OTSU) Segmentation for Locating and Recognize Satellite Image Remote Sensing for Aircraft
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2016
卷号：5
期号：5
页码：8905
DOI：10.15680/IJIRSET.2016.0505327
出版社：S&S Publications
摘要：This paper proposes the application different kinds of feature extractors technique to recognize &locating the aircraft satellite image. Recognition of object (Aircraft) in an image based on the combination of featureextractors which contain of fast Fourier transform, discrete wavelet transform & discrete curvelet transform in additionto the correlation on shape analysis. Also an object can be recognized with help of texture or appearance featuresthrough Scale invariant feature transform (Wavelet Transform) and OTSU (Multi Scale segmentation), To justify thecorrect amount of each feature extractor, we perform per of the mentioned transforms to input images, precisely. Theused classifier in this paper using Detect Fuzzy Clustering and the results of this test show, that the right recognitionrate of aircraft in this recognition system, at the time of using curve let transform and all curvelet coefficients is 100%.For decreasing the dimension of feature vectors more & choosing the best features we've used of interclass variancecriteria to intra class variance criteria. As a result of this performance, the size of feature vectors will be extremelydecreased. Then, we perform our final impact feature vectors (the best curvelet coefficients or the best waveletcoefficients or the best Fourier coefficients) to the fuzzy and neural network.
