基于相对熵的图像阈值分割的改进共现矩阵特征空间

Computer Graphics, Imaging and Visualisation (CGIV 2007) Pub Date : 2007-08-14 DOI:10.1109/CGIV.2007.49

I. El-Feghi, N. Adem, M. Sid-Ahmed, M. Ahmadi

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引用次数: 6

摘要

本文提出了一种适用于噪声背景图像的阈值分割技术。该算法采用改进的共现矩阵作为特征空间。阈值是通过最大化相对熵得到的。实验结果表明，该方法优于其他阈值分割技术，特别是在输入图像背景中存在噪声的情况下。

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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Improved Co-occurrence Matrix as a Feature Space for Relative Entropy-based Image Thresholding

In this paper, a thresholding technique suitable for noisy background images is proposed. The proposed algorithm uses an improved co-occurrence matrix as feature spaces. The threshold value is obtained by maximizing the relative entropy. Experimental results show that the proposed method outperforms other thresholding techniques especially on the presences of noise in the background of the input image.

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Computer Graphics, Imaging and Visualisation (CGIV 2007)

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