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Performance evaluation of image retrieval using Enhanced 2D Dual Tree Discrete Wavelet Transform

机译:使用增强型二维双树离散小波变换的图像检索性能评估

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摘要

Content based image retrieval is emerging as an important area of research in image processing. Based on dual tree discrete wavelet transform, and minimum distance classification the feature vectors are extracted and similarity is found in existing research. This paper proposes a new method for improving the performance of image retrieval system using Enhanced 2D Dual Tree Discrete Wavelet Transform (E-2D-DT-DWT). The number feature vectors are increased with higher levels of decomposition in the extraction method. In addition to Euclidean distance as the distance measure of feature vectors, this paper also proposes minimum distance classification for an efficient and effective distance classification. Performance evaluation is done using two parameters precision and recall. The experimental results show that precision and recall is improved with the proposed method.
机译:基于内容的图像检索正在成为图像处理研究的重要领域。基于对偶树离散小波变换,在最小距离分类的基础上,提取特征向量,并在现有研究中找到相似性。本文提出了一种使用增强型二维双树离散小波变换(E-2D-DT-DWT)改善图像检索系统性能的新方法。在提取方法中,随着分解程度的提高,特征向量的数量也随之增加。除了欧几里得距离作为特征向量的距离度量之外,本文还提出了最小距离分类,以实现有效的距离分类。使用两个参数Precision和Recall对性能进行评估。实验结果表明,该方法提高了查准率和查全率。

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