Imagemap simplification using mathematical morphology

For a variety of mapping applications, images are the most important primary data sources. In photogrammetry and remote sensing, particular procedures are used for image and map data integration in order to perform change detection and automatic object extraction. The recognition of an object in an image is a complex task that involves a broad range of techniques. In general, three steps are used in this study. The first step is segmentation to object regions of interest. In this step, regions which may contain unknown objects, have to be detected. The second step focuses on the extraction of suitable features and then extraction of objects. The main purpose of feature extraction is to reduce data by means of measuring certain features that distinguish the input patterns. The final step is classification. It assigns a label to an object based on the information provided by its descriptors. At the end of segmentation stage, the images are too still complex. So it is necessary to simplify image for further processes. In this paper, investigation is made on the mathematical morphology operators for simplification of a gray-scale image or imagemap. Then an structure element, () L 4 , is applied on binary images to extract the skeletonized image. In this stage, there will remain lots of skeletal legs in the resultant image. Then in the next step, another structure element, () E 4 , is applied on skeletonized image to remove the remaining skeletal legs. The resulting thinned image may be extracted and then converted to vectors. The vector data may be input to a geographic information system (GIS) for further analysis. The program for this project is developed in visual c++ language under windows 98 operating system.