A region-based shape descriptor using Zernike moments
A region-based shape descriptor using Zernike moments
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DOI：
10.1016/s0923-5965(00)00019-9
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发表时间：
2000-09-01
影响因子：
3.5
通讯作者：
Kim, YS
中科院分区：
文献类型：
--
作者：
Kim, WY;Kim, YS
为了从大型图像数据库中检索图像，描述符应具有尺度和旋转不变性。它还必须具有足够的鉴别能力和抗噪声能力，以便从大型图像数据库中检索。Zernike矩描述子具有旋转不变性、鲁棒性、表达效率高、计算速度快和多层次表达等优点。在本文中，我们表明，Zernike矩可以作为一个有效的描述的全球形状的图像在一个大型的图像数据库。实验结果表明，本文提出的形状描述子在6,000幅图像的数据库中进行了各种变换下的精确匹配和基于相似性的检索，结果表明，本文提出的形状描述子能够有效地表示形状。(C)2000 Elsevier Science B. V.保留所有权利。
In order to retrieve an image from a large image database, the descriptor should be invariant to scale and rotation. It must also have enough discriminating power and immunity to noise for retrieval from a large image database. The Zernike moment descriptor has many desirable properties such as rotation invariance, robustness to noise, expression efficiency, fast computation and multi-level representation for describing the shapes of patterns. In this paper, we show that the Zernike moment can be used as an effective descriptor of global shape of an image in a large image database. The experimental results conducted on a database of about 6,000 images in terms of exact matching under various transformations and the similarity-based retrieval show that the proposed shape descriptor is very effective in representing shapes. (C) 2000 Elsevier Science B.V. All rights reserved.