A New Automatic Road Extraction Technique using Gradient Operation and Skeletal Ray Formation

Abstract

The usage of satellite images and extracting road from the imagery becomes very significant in the services related to road transportation such as maintenance, creation and so on. The literature has numerous works for road extraction but very less contribution is found in dealing with rural areas. In the previous work, ANN-based road extraction technique has been proposed. However to improve the performance of the technique, herewith a new road extraction technique is proposed. The proposed technique extracts the road mainly with the contribution of gradient operation and skeletal ray formation over the subjected satellite imagery. As minor operations, filtering and thresholdbased processing is performed. At the end, a coloring is performed followed by a morphological operation to extract the final road from the subjected rural areas. The proposed technique is tested with different satellite images and the results are compared against the previous technique. The comparative analysis show that the proposed technique outperforms rather than the previous technique in terms of standard performance measures such as completeness, correctness and quality.

ANN based GUI to Classify Satellite Images for Remote Sensing

“…As this information is to be classified from the images that are to be acquired from satellites, hence, it is mandatory to develop an algorithm which accurately classifies such information from high-resolution satellite image. A sample high-resolution satellite image is shown in figure 1 below: Figure 1: High Resolution Satellite Image [3] It is also pertinent to note that Artificial Neural Network (ANN) is widely used for feature classification in digital images. The prime advantage of using ANN is its capability to handle high resolution images with less computational complexity and best error tolerance.…”