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Content-based blur image retrieval using quaternion approach and frequency adder LBP
Multidimensional Systems and Signal Processing ( IF 2.5 ) Pub Date : 2019-04-16 , DOI: 10.1007/s11045-019-00643-w
Komal Nain Sukhia , M. Mohsin Riaz , Abdul Ghafoor

The paper presents a content based image retrieval scheme based on feature extraction and weighing. Features are extracted using frequency adder based local binary pattern and blur detection metric which are then optimally combined using a weighing scheme. Simulations are performed on modified Wang and KTH-TIPS databases, which include images from four different classes of blur respectively. Comparison of simulation results with the state-of-the-art techniques show better retrieval precision and recall values for proposed technique.

中文翻译:

使用四元数方法和频率加法器 LBP 基于内容的模糊图像检索

本文提出了一种基于特征提取和加权的基于内容的图像检索方案。使用基于频率加法器的本地二进制模式和模糊检测度量提取特征,然后使用加权方案进行最佳组合。模拟是在修改后的 Wang 和 KTH-TIPS 数据库上执行的,它们分别包括来自四种不同模糊类别的图像。模拟结果与最先进技术的比较表明所提出的技术具有更好的检索精度和召回值。
更新日期:2019-04-16
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