基于纹理特征的高效图像检索

Fazal-e-Malik, B. Baharudin
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引用次数: 7

摘要

提出了一种快速准确的基于内容的图像检索算法。该算法基于统计纹理特征从数据库中检索相似图像。其基本思想是将RGB彩色图像转换为灰度图像,以降低计算速度,提高效率。灰度图像被分成不同大小的块。统计纹理特征的提取是利用各块中强度等级的概率分布。在实验中,对不同块大小方法的特征提取效率和图像检索精度进行了测试。使用Corel数据库进行测试。结果表明,本文提出的CBIR算法在效率和精度方面都有较高的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient image retrieval based on texture features
A quick and accurate algorithm for content-based image retrieval (CBIR) is proposed in this paper. The retrieval of the similar images using proposed algorithm from the database is based on the statistical texture features. The basic idea is to convert the RGB color image into grayscale image to reduce the computation speed and increase efficiency. The grayscale image is divided into blocks of different sizes. The statistical texture features are extracted by using the probability distribution of intensity levels in all blocks. In the experiment, the efficiency of feature extraction and accuracy of the image retrieval are measured for different block size methods using the proposed algorithm. The Corel database was used for testing. As a result the proposed CBIR algorithm provided higher performance in terms of efficiency and accuracy.
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