Title :
Skyline localization for mountain images
Author :
Yao-Ling Hung ; Chih-Wen Su ; Yuan-Hsiang Chang ; Jyh-Chian Chang ; Hsiao-Rong Tyan
Author_Institution :
Inst. ofinformation Sci., Taiwan
Abstract :
In this paper, we propose a novel method for automatically locating the skyline that represents the shape of mountains. The appearances of mountain and sky are variable because of the weather, season or region. In order to extract the skyline of mountains under complicated and variable circumstances, support vector machine (SVM) is applied for the prediction of a part of the skyline between sky region and mountain region by using the color, statistics features and location information of edge. Then, the linking of incomplete fragments of skyline is formulated as a shortest path problem and solved by dynamic programming strategy. Our experimental results demonstrate that the proposed method is accurate and robust.
Keywords :
dynamic programming; edge detection; feature extraction; image colour analysis; statistical analysis; support vector machines; SVM; automatic skyline localization; color feature; dynamic programming strategy; edge location information; incomplete skyline fragment linking; mountain images; mountain region; mountain shape representation; mountain skyline extraction; shortest path problem; sky region; statistics feature; support vector machine; variable mountain appearance; variable sky appearance; Abstracts; Image edge detection; Image segmentation; Indexes; Support vector machines; Skyline extraction; support vector machine;
Conference_Titel :
Multimedia and Expo (ICME), 2013 IEEE International Conference on
Conference_Location :
San Jose, CA
DOI :
10.1109/ICME.2013.6607424