基于区域的二叉树图像分类

International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 2003-12-01 DOI:10.1109/ICNNSP.2003.1279254

Zhiyong Wang, D. Feng, Z. Chi

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引用次数: 8

摘要

由于缺乏有效的表示，图像分类是一个非常具有挑战性的问题。本文提出了一种结合数据结构自适应处理的基于区域的二叉树表示方法来解决这一问题。对图像进行分割后，利用区域合并的方法建立二叉树来表征图像的内容。最后，采用数据结构自适应处理算法对二叉树进行分类。在7个类别的风景图像上的实验结果表明，这种基于区域的结构表示优于我们之前基于四叉树表示的工作。

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Region-based binary tree representation for image classification

Image classification is a very challenging problem due to lack of effective representations. In this paper, a region-based binary tree representation incorporating with adaptive processing of data structures is proposed to address this problem. After an image is segmented, a binary tree is established to characterize its contents by using region merging method. Finally, an adaptive processing of data structure algorithm is employed to perform the classification task with binary tree representation. Experimental results on seven categories of scenery images show this region-based structural representation is superior to our previous work based on quadtree representation.

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International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003

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