An automatic system of detecting changes in aerial images using ANN based contourlet transform

H. Yaşar, Rıdvan Safa Hatipoğlu, M. Ceylan
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引用次数: 1

Abstract

The obtaining of the aerial images got easy thanks to technological developments in the field of unmanned aerial vehicles and these images were began to be used frequently in the field of image processing. Automatic changes detection from aerial images is among the most important study fields. An automatic system for changes detection has been proposed by using contourlet transform and artificial neural network (ANN) in this study. The contourlet transform is applied to the reference image in the first phase of the system consisting of two phases. Mean, variance, standard deviation and skewness values were calculated from the obtained sub-image matrix and seven image feature vectors are formed by using these statistical values and combinations. The numerical equivalents of the reference image were obtained by using the feature vectors by ANN. The same procedures were applied to the image that its exchange will be examined in the second phase of the system. The change between numerical provisions of the reference image and the image to be examined compared to the threshold value set by the user and automatic changes detection was performed. It was found that the changes in numerical results obtained at the end of the study overlap with the changes in aerial images.
基于神经网络的轮廓波变换的航空图像变化自动检测系统
随着无人机领域技术的发展,航空图像的获取变得容易,并开始在图像处理领域得到频繁的应用。航空图像的自动变化检测是一个重要的研究领域。本文提出了一种基于contourlet变换和人工神经网络(ANN)的自动变化检测系统。在由两阶段组成的系统的第一阶段,对参考图像进行轮廓波变换。从得到的子图像矩阵中计算均值、方差、标准差和偏度值,利用这些统计值和组合形成7个图像特征向量。利用特征向量,通过人工神经网络获得参考图像的数值等值。同样的程序也适用于将在该系统的第二阶段审查其交换的图象。将参考图像的数值规定与待检测图像之间的变化与用户设置的阈值进行比较,并进行自动变化检测。研究结束时得到的数值结果的变化与航拍图像的变化是重叠的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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