Infrared Object Recognition Based on Monogenic Features and Multiple Kernel Learning
点击次数：
所属单位：自动化学院
发表刊物：2018 IEEE 3RD INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC)
关键字：infrared object recognition monogenic feature multiple kernel learning
摘要：Infrared object recognition is an important branch in the field of image processing and computer vision. This paper proposes a novel infrared object recognition method based on monogenic features and multiple kernel learning. Specifically, the proposed features are mainly derived from the ideas of the monogenic signal. The applicability of the monogenic signal within the field of infrared object recognition is demonstrated by its capability of capturing both the spectral information and spatial localization with compact support. Second, to reduce the dimensionalities of the monogenic features, the principal component analysis is applied. Third, the reduced monogenic features are adaptively fused in the multiple kernel learning framework. At last, a multiple kernel learning support vector machine classifier is designed for recognizing the infrared objects. The experimental results show that the proposed method leads to good infrared object recognition performance.
是否译文：否
发表时间：2018-01-01
合写作者：刘文波,Wang, Xin
通讯作者：郭宁晨