基于小波的图像索引与检索——基于分割k均值聚类的分割

V. Natarajan
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引用次数: 1

摘要

使用图像作为身份工具正在各种应用程序中实现。虹膜图案、拇指印等图像正被用作人们的身份识别工具。当查询目标图像时,需要一个复杂的算法来索引和检索相应的图像。本文讨论了一种基于小波的图像索引算法。采用小波域的k均值分割算法对图像进行分割。它用于在图像中找到合适的片段,为进一步的处理提供帮助。提取特征向量并存储在数据库中,用于查询和检索。对查询图像也采用同样的方法进行处理,提取特征向量。将该向量与数据库中存储的向量进行比较,并根据相似性值检索相关图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Indexing and Retrieval of Images Using Wavelets - Segmentation Using Bisecting K-Means Clustering
Using images as identity tool is being implemented in various applications. Images like iris pattern, thumb impressions are being used as identity tools for persons. A sophisticated algorithm is required to index and retrieve appropriate image when queried with a target image. This paper discusses one such image indexing algorithm using wavelets. The images are segmented using Bisecting K-Means algorithm in wavelet domain. It is used to find out appropriate segments in the images and helps for further processing. Feature vectors are extracted and stored in the database for querying and retrieval purpose. Query image is also processed in the same method and the feature vector is extracted. This vector is compared against vectors stored in the database and relevant images are retrieved based on the similarity value.
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