综合PHOG和LWT的图像检索算法  

An Image Retrieval Method Based on PHOG and LWT

作　　者：弓云峰[1] 崔得龙[1] 

机构地区：[1]广东石油化工学院,茂名525000

出　　处：《包装工程》2017年第15期202-206,共5页Packaging Engineering

基　　金：国家自然科学基金(61473331);广东省云机器人工程中心项目(660010);茂名市石油化工自动化工程技术研究开发中心项目(517013)

摘　　要：目的研究物体的形状特征在图像描述及图像检索中的区分度和检索性能。方法设计一种综合PHOG形状和提升小波变换的图像检索算法。算法首先对原始图像进行极坐标系方向归一化,提取图像旋转不变特征;其次提取分层图像的PHOG形状特征;然后提取分层图像低频变换系数均值和方差作为提升小波变换特征;最后将各种特征进行融合并用于图像检索,并定义距离衡量公式。结果通过文中设计算法提取的图像形状特征可使各标准测试图像间距离均值为0.2352。结论在Corel图像集上的检索实验结果优于RIM算法和FWTH算法,表明文中算法图像检索领域具有一定的应用前景。The work aims to study discriminative power and retrieval performance of shape feature of the objects in image description and image retrieval. An image retrieval method synthesizing PHOG shape and lifting-based wavelet transform was designed. Firstly, the orientation normalized polar coordinate system of the original image was achieved to extract the image rotational invariant features. Secondly, PHOG shape feature of layered image was extracted. Then, the mean value and variance of low-frequency transform coefficient of the layered image were extracted as the transform feature of the lifting-based wavelet. Finally, all kinds of features were synthesized and used for image retrieval, and the distance measurement formula was defined. The image shape features extracted by the designed algorithm proposed herein could enable the mean value of distances between all standard test images to be 0.2352. The retrieval experiment results on Corel image set are superior to RIM algorithm and FWTH algorithm, which indicates that the proposed algorithm has certain application prospects in the field of image retrieval.

关 键 词：PHOG 形状特征 提升小波 图像检索 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]