کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
535777 870379 2012 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Target detection of ISAR data by principal component transform on co-occurrence matrix
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Target detection of ISAR data by principal component transform on co-occurrence matrix
چکیده انگلیسی

Issue of automated target detection in ISAR can be stated as what features enhance objects of interest from the rest of the data. Much experimentation done in this area have used Fourier transforms for preprocessing the raw signal data. Generally the ISAR data are comes with a matrix of complex number values and therefore intuitive logic appears to favor a Fourier transform. A hypothesis was made that a Fourier transform in preprocessing may mask some data that could be part of feature used to threshold the object from background. Thus a trial was done on MATLAB simulated ISAR data to see if such data can be transformed into a matrix to visualize objects by preprocessing with principle component transform followed by some modification conventional thresholding techniques i.e. gray level co-occurrence matrix. Since it would be difficult to do so in complex valued matrices, these matrices had been decomposed to real valued and the imaginary valued matrices separately. Advantages of simulated data were that variables could be defined and changes in preprocessing transform and thresholding result could be compared with significant accuracy before a trial with actual performance of ISAR imagery. The preliminary result in this paper does show that preprocessing transform need not be Fourier. Principle component transform may bring about features that enhance thresholding values for Automatic target detection. Thresholding in conventional methods is done by finding a fixed value to create a binary image highlighting the object. In the modification proposed here single value thresholding objects and then spatially locating the object in a binary matrix may circumvented.


► We postulate ISAR data may not require Fourier transform for visualization.
► PCT provides a good alternative for processing ISAR signal data matrix.
► Additional GLCM processing enhances automated target detection without creating specific thresholding cut offs.
► This work has been done on simulated ISAR data needs confirmation by actual experimentation.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 33, Issue 13, 1 October 2012, Pages 1682–1688
نویسندگان
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