Blurred Image Detection In Drone Embedded System

Ratiba Gueraichi, A. Serir
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引用次数: 3

Abstract

This paper deals with the detection of blurred images that may eventually be captured by a drone. The embedded system should be able to measure the amount of blur affecting the images in order to decide whether to acquire the scene again or not. For this purpose, we have developed a simple model based on Discrete Cosine Transform (DCT) associated to Support Vector Machine Classifier SVM, to classify images into three categories and thus detect strongly, moderately and slightly blurred images. The proposed system has been tested on 550 images captured by a drone. The obtained results are very conclusive.
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无人机嵌入式系统中的模糊图像检测
本文讨论了可能最终由无人机捕获的模糊图像的检测。嵌入式系统应该能够测量影响图像的模糊量,以便决定是否重新获取场景。为此,我们开发了一个基于离散余弦变换(DCT)的简单模型,该模型与支持向量机分类器SVM相关联,将图像分为三类,从而检测出强烈、中度和轻度模糊的图像。该系统已经在一架无人机拍摄的550幅图像上进行了测试。所得结果是很有说服力的。
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