关键词: 天际线检测, 支持向量机, Canny边缘检测, 线性五邻域搜索算法

Abstract: Focused on the issue of high robustness and high accuracy detection of skyline, a skyline detection algorithm based on multiple feature extraction and edge correction is proposed. The multi-eigenvalues of the training pixels randomly in sky and non-sky regions are extracted according to texture information and color information. Then, the multi-eigenvalues are used to train a classifier based on Support Vector Machine（SVM） to obtain the initial position coordinates of skyline. Next, the Canny operator method is used to detect the edge of the gray image. And the linear five neighborhood search algorithm is used to correct the position of the initial coordinate, finally skyline coordinates of original images are obtained. The proposed algorithm is tested on the Web Set and the Basalt Hills Set, the results indicate that the proposed method can effectively detect the skyline coordinates, reduce the interference of other pixels to some extent and make the skyline more smoothly.

Key words: skyline detection, Support Vector Machine（SVM）, Canny edge detection, linear five-neighborhood search algorithm