1. 北京理工大学计算机学院,北京,100081
2. 北京理工大学光电学院北京市混合现实与新型显示工程技术研究中心,北京,100081
3. 北京理工大学计算机学院,北京,100081
4. 北京理工大学光电学院北京市混合现实与新型显示工程技术研究中心,北京,100081
纸质出版:2014
移动端阅览
桂振文, 刘越, 陈靖, 等. 一种适用于智能手机的图像识别算法[J]. 电子学报, 2014,42(8):1487-1494.
GUI Zhen-wen, LIU Yue, CHEN Jing, et al. A Novel Image Recognition Algorithm for Smartphones[J]. Acta Electronica Sinica, 2014, 42(8): 1487-1494.
桂振文, 刘越, 陈靖, 等. 一种适用于智能手机的图像识别算法[J]. 电子学报, 2014,42(8):1487-1494. DOI: 10.3969/j.issn.0372-2112.2014.08.005.
GUI Zhen-wen, LIU Yue, CHEN Jing, et al. A Novel Image Recognition Algorithm for Smartphones[J]. Acta Electronica Sinica, 2014, 42(8): 1487-1494. DOI: 10.3969/j.issn.0372-2112.2014.08.005.
针对目前常用的图像识别算法运算复杂和内存占用量大,不能很好的应用于移动平台等问题,本文提出了一种适用于智能手机的图像识别算法:首先,通过使用BRISK特征点检测算法提取图像特征和低字节的FREAK描述符对特征进行表述,解决了特征检测时间长和特征描述符内存占用大的问题;其次,将智能手机的重力信息添加到图像特征中改善了BRISK特征的区分能力,解决了相似结构特征难以区分的问题;最后,建立描述符的多级索引,实现相似描述符的快速查找,解决了描述符匹配问题.实验结果表明,本文提出的算法能有效地运行在资源受限的智能手机上实现对场景的实时识别.
At present
the conventional image recognition algorithm cannot be well applied to mobile platforms due to their large computational cost and high storage requirements.In this paper
a novel image recognition algorithm for smartphone is proposed:Firstly
BRISK detection algorithm and low-byte FREAK descriptor are used to extract image feature and represent image respectively
which solves the problems of long detection time and large memory footprint;Secondly
BRISK features are improved to accomplish the distinction between the similar structure features by adding the gravity information of smartphone to the image feature;Finally
multi-level index of descriptors have been established to achieve fast finding on similar descriptors which solve the matching problem.The experimental results show that the proposed algorithm can be effectively run on the resource-constrained general smartphone to achieve scene recognition in real-time.
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