Automatic Road Digitizing of Segmented Aerial Images for Urban Areas Based on K-means and Hough Transformation

In Geographical Information System (GIS), digitiz-

ing is an exhausting and time consuming process which is used for

digital mapping and map updating. Popularity of mobile services

and autonomous vehicles technology based on roads network

increase the need for road automatic digitizing. Last years,

deep-learning gave excellent results on roads segmentation from

aerial and satellite imagery [1], that highlighted the automatic

digitizing. In this paper statistical method is applied to extract

roads from segmented images, and tested with images for three

different scenes and gave an average accuracy of 86 percent.