利用新规则矩对伸长和收缩图像进行分类

Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94) Pub Date : 1994-10-01 DOI:10.1109/ICNN.1994.374880

P. Raveendran, S. Jegannathan, S. Omatu

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引用次数: 8

摘要

本文提出了一种对被拉长或收缩的图像进行分类的技术。这个问题是用常规矩来表述的。结果表明，当图像在x和y方向上进行不相等缩放时，常规矩不变量不再保持不变。提出了一种在这种不等尺度下形成不变矩的方法。计算机图像仿真结果验证了所提方法的有效性。

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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Classification of elongated and contracted images using new regular moments

This paper presents a technique to classify images that have been elongated or contracted. The problem is formulated using conventional regular moments. It is shown that the conventional regular moment-invariants remain no longer invariant when the image is scaled unequally in the x- and y-directions. A method is proposed to form moment-invariants that do not change under such unequal scaling. Results of computer simulations for images are also included verifying the validity of the method proposed.<>

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Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)

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