【摘要】 无人机着陆点识别是图像识别算法的一个重要应用领域,提出了一种基于自然地貌图像的着陆点识别算法。首先用Contourlet变换对基准图库图像进行Contourlet变换,得到不同分辨率下的高频和低频子图;然后分别提取各子图的Hu矩特征;根据各特征识别率的不同进行特征筛选,建立特征识别库;接着进行k-mean法特征匹配。通过对基准图库中的单一地貌图像和测试图像库中的复杂地貌图像的识别实验,验证了算法的有效性。更多还原

【Abstract】 Unmanned Aerial Vehicle(UAV)landing point recognition is an important application of image recognition algorithms.This paper put forward a landing point recognition algorithm based on natural landform.The standard graphics library was decomposed by Contourlet decomposition firstly and the low-frequency subimage and band-pass subimage were obtained in different resolutions,and then the Hu invariant moments were extracted from each sub-graph respectively.The feature recognition library was built by feature selection according to the different recognition rate,then feature matching was done with the k-mean method.The recognition experiments which involve single grassland images and complex landform images in testing gallery show that the algorithm of this paper is effective for image recognition.更多还原