Object Oriented Approaches in Segmentation of Grayscale Images

Detection of the geometric forms of different land covers relies on segmentation of satellite images which often is one of the main tasks that need to be solved in that process. Lately a great variety of methods for segmentation of such images was worked out. The aim of this study is to compare the applicability of two modern methods for image processing in the extraction of information from satellite images - namely object-oriented approach and mathematical morphological method.
Mathematical morphology can be considered as geometric approach in image processing and analysis with a strong mathematical aspect. Originally, it was developed as a powerful tool for shape analysis in binary and, later, satellite images.
The applications of the mathematical morphological methods could be summarized as follows: satellite images segmentation; use of morphological filters for generation of digital elevation models (DEMs); satellite images classification.
The second method considered is the multivariate segmentation realized by the eCognition package. This patented algorithm is used as starting point for comparison of the newly developed ones.
Both methods were applied for segmentation of a satellite image taken from central Bulgarian region. The obtained results were compared and the advantages and disadvantages of morphological method are discussed. Conclusions about applicability of morphological methods for segmentation of satellite images are also made.