Improving Multi-level Morphological Active Contour for Tree Crowns Detection and Delineation using spectral information

• Main Authors: Yi-Ling Chen, 陳怡玲
• Other Authors: Chao-Cheng Wu
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/axb27p

碩士 === 國立臺北科技大學 === 電機工程系研究所 === 101 === Forests in Taiwan distribute vertically along the central region and can be categorized into broadleaved, mixed, and conifer forests. Terrain features make manual inspection of forests nearly impossible. By utilizing remote sensing data, the amount of field sampling could be significantly reduced. However, the visual interpretation is labor-intensive and heavily dependent on the interpreter’s experience. A new algorithm, called multi-level morphological active contour algorithm (MMAC), has been proposed by Prof. Lin, to address these issues in 2011. The MMAC could effectively increase recognition rate of individual tree in mountainous areas, which is the common case in Taiwan. However, the design of algorithm could only cope with Lidar images, which contains altitude information of ground objects. If the RGB or multispectral images were applied, the performance of MMAC would drop significantly. This thesis exploits spectral information to eliminate restriction of MMAC which only runs on lidar images. Multispectral analysis and classifiers would be exploited to provide spectral features and classification of tree tops and their crowns. The contribution of this thesis would extend the applications of MMAC to traditional and multispectral images, and further shed light on large scale remote sensing images.