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基于特征距离与极谐变换的图像检索算法
李俊梅, 万 勇, 李祥琴
荆楚理工学院 计算机工程学院,湖北 荆门 448000
摘要:
为提高图像在数据集中的检索准确度,设计了基于加权距离与多元极谐变换的图像检索算法。在查询图像的色调-饱和度-亮度(HSV)空间内,提取其颜色特征;并引入贝塞尔K分布与非下采样Shearlet变换(NSST)方法得到查询图像的纹理特征,改善其对模糊与亮度变换等操作的稳健性;借助四元极谐变换(QPHT)机制,将图像的QPHT模系数视为形状特征,提高对噪声与几何变换的鲁棒性。通过融合这3种特征,分别计算查询图像与数据库图像之间对应的特征距离,并赋予三者对应的权重,以测量两幅图像之间的相似度,从而准确输出检索结果。测试数据显示,与当前基于内容的图像检索技术相比,所提算法具备更高的检索准确度和鲁棒性,在多种几何变换攻击下,仍可以准确检索出目标。
关键词:  图像检索  非下采样Shearlet变换  HSV空间  颜色特征  纹理特征  四元极谐变换  形状特征  加权距离
DOI:10.11805/TKYDA2019195
分类号:
基金项目:湖北省教育厅产学研合作基金资助项目(201801329007);荆门市科技局科研基金资助项目(2019YDKY078)
Image retrieval based on weighted feature distance and multivariate polar harmonic transform
LI Junmei, WAN Yong, LI Xiangqin
College of Computer Engineering,Jingchu University of Technology,Jingmen Hubei 448000,China
Abstract:
n order to improve the retrieval accuracy of images in datasets, an image retrieval algorithm based on weighted distance and multivariate polar harmonic transformation is designed by making full use of the texture and shape features of the query object. The color features are extracted in the Hue-Saturation–Value(HSV) space of the query image. Bessel K-distribution and Non-down Sampled Shearlet Transform(NSST) are introduced to obtain the texture features of the query image for improving its robustness to blur and brightness transformation. With the help of the Quaternion Polar Harmonic Transform(QPHT) mechanism, the QPHT modulus of an image is regarded as a shape feature to improve the robustness to noise and geometric transformation. By fusing the three features, the corresponding feature distance between the query image and the database image is calculated, and the corresponding weight of them is given to measure the similarity so as to output the retrieval results accurately. The test data show that this algorithm has higher retrieval accuracy and robustness, which can still accurately retrieve the target under various geometric transformation attacks compared with the current content-based image retrieval technology.
Key words:  image retrieval  Non-down Sampling Shearlet Transform  HSV space  color feature  texture feature  Quaternion Polar Harmonic Transform  shape feature  weighted distance

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