计算机工程与应用2018，Vol.54Issue(3)：206-211,6.DOI:10.3778/j.issn.1002-8331.1706-0267
基于兴趣域检测的空间金字塔匹配图像分类
Image classification based on region of interest dection and spatial pyramid matching
摘要
Abstract
In the process of image classification, the image region containing object which plays a decisive role is indefinite in both position and scale, and it can not get a high accuracy of image classification by using Spatial Pyramid Matching (SPM)directly. Therefore, a method for improving the performance of image classification based on Region of Interest (ROI)detection and Spatial Pyramid Matching(SPM)is proposed. This method first makes use of localization results of detector, and it verifies feasibility of using a state-of-the-art object detection algorithm to separate the goals of image and background for image classification. Then, a method which is called coarse object alignment matching is used to construct spatial histogram features for these two regions separately based on SPM. Finally, the scores provided by real detector and Support Vector Machine(SVM) are combined to rescore for the final result. Experimental results demonstrate that the mean average precision of proposed method has been promoted over 12 percent than the standard SPM. Compared to three state-of-the-art methods, the proposed method gets the highest mean average precision, and gets the highest average precision at more than half image categories.关键词
图像分类/空间金字塔匹配/兴趣域/特征直方图/平均准确度均值Key words
image classification/spatial pyramid matching/region of interest/spatial histogram features/mean average precision分类
信息技术与安全科学引用本文复制引用
周华兵,朱国家,张彦铎,任世强..基于兴趣域检测的空间金字塔匹配图像分类[J].计算机工程与应用,2018,54(3):206-211,6.基金项目
国家自然科学基金(No.41501505). （No.41501505）
