A procedure for semi-automatic segmentation in OBIA based on the maximization of a comparison index
Abstract:
In an Object Based Image Analysis Classification (OBIA) process, the quality of the classification results are highly dependent on segmentation. However, a high number of the studies that make use of an OBIA process find the segmentation parameters by making use of trial-and-error methods. It is clear that a lack of a structured procedure to determine the segmentation parameters produces unquantified errors in the classification. This paper aims to quantify the effects of using a semi-automatic approach to determine optimal segmentation parameters. To this end, an OBIA process is performed to classify land cover types produced by both a manual and an automatic segmentation. Even though the classification using the manual segmentation outperforms the automatic segmentation, the difference is only 2%. Since the automatic segmentation is performed with optimal parameters, a procedure to accurately determine those parameters must be performed to minimize the error produced by a misjudgment in the segmentation step. © 2014 Springer International Publishing.
Año de publicación:
2014
Keywords:
- segmentation parameters
- OBIA
- comparison index
- segmentation
- SUPPORT VECTOR MACHINES
- classification
Fuente:
Tipo de documento:
Conference Object
Estado:
Acceso restringido
Áreas de conocimiento:
- Visión por computadora
- Algoritmo
Áreas temáticas:
- Sistemas