Road Extraction using Connected Component Techniques

Abstract

Extraction of Roads, Rivers and other map objects is an important step in many military and civilian applications. In this process the information is extracted which possess high efficiency and accuracy and is fed into GIS (Geographical Information System). In this paper, we have explored different algorithms with better efficiency and accuracy. Road extraction can take place for two kinds of roads namely: urban and non-urban roads. Urban roads are more complex to analyze because of their architectural complexity, occlusions created by trees, heavy traffic and extensive network, whereas non-urban roads are easier to analyze because of less structural         complexity. The proposed algorithm exploits the properties of road segments to develop customized operators to accurately derive the road segments. The customized operators include directional morphological    enhancement, directional segmentation and thinning. The proposed algorithm is systematically evaluated on the basis of variety of images and compared with other algorithms (Canny, Sobel, Roberts, and Morphological Segmentation). The results demonstrate that the algorithm proposed is both accurate and efficient. The data and performance measures such as completeness and correctness are calculated together with other parameters which are Peak Signal to Noise ratio, Normalized Cross Correlation, Structural Content and a statistical analysis of the comparison is presented.