Automatic main road extraction from high resolution satellite imageries by means of particle swarm optimization applied to a fuzzy-based mean calculation approach

Manual extraction of road network by human operator is an expensive and time-consuming procedure. Alternatively, automation of the extraction process would be a great advancement. For this purpose, an automatic method is proposed to extract roads from high resolution satellite images. In this study, using few samples from road surface, a particle swarm optimization is applied to a fuzzy-based mean calculation system to obtain road mean values in each band of high resolution satellite colour images. Then, the images are segmented using the calculated mean values from the fuzzy system. Optimizing the fuzzy cost function by particle swarm optimization enables the fuzzy approach to be the best mean value of road with sub-grey level precision. Initially, this method was applied to simulated images where the calculated mean values are consistent with the hypothetic mean values. Application of the method to IKONOS satellite images has shown a prospective outcome for automatic road extraction. Mathematical morphology is subsequently used to extract an initial main road centreline from the segmented image. Then, small redundant segments are automatically removed. The quality of the extracted road centreline indicates the effectiveness of the proposed approach.

[1]  Gonzalo Pajares,et al.  A wavelet-based image fusion tutorial , 2004, Pattern Recognit..

[2]  Curt H. Davis,et al.  An integrated system for automatic road mapping from high-resolution multi-spectral satellite imagery by information fusion , 2005, Inf. Fusion.

[3]  Richard R. Forster,et al.  Fusion of hyperspectral and radar data using the IHS transformation to enhance urban surface features , 2003 .

[4]  Emmanuel P. Baltsavias,et al.  Object extraction and revision by image analysis using existing geodata and knowledge: current status and steps towards operational systems☆ , 2004 .

[5]  Kaizhong Zhang,et al.  A Wavelet Transform Based Method for Road Centerline Extraction , 2004 .

[6]  Ali Azizi,et al.  Automatic road-side extraction from large scale imagemaps , 2002 .

[7]  A. Mohammadzadeh,et al.  Road extraction based on fuzzy logic and mathematical morphology from pan‐sharpened ikonos images , 2006 .

[8]  Randy L. Haupt,et al.  Practical Genetic Algorithms , 1998 .

[9]  J. Serra,et al.  An overview of morphological filtering , 1992 .

[10]  Anthony Stefanidis,et al.  DIFFERENTIAL SNAKES FOR CHANGE DETECTION IN ROAD SEGMENTS , 2001 .

[11]  Anthony Stefanidis,et al.  Quality-aware deformable models for change detection , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[12]  Stefan Hinz,et al.  Automatic extraction of urban road networks from multi-view aerial imagery , 2003 .

[13]  Jean Serra,et al.  Image Analysis and Mathematical Morphology , 1983 .

[14]  Anthony Stefanidis,et al.  Self-organised clustering for road extraction in classified imagery , 2001 .

[15]  E. Baltsavias,et al.  Automatic Extraction of Man-Made Objects from Aerial and Space Images (II) , 1995 .

[16]  Juan B. Mena,et al.  State of the art on automatic road extraction for GIS update: a novel classification , 2003, Pattern Recognit. Lett..

[17]  Thierry Ranchin,et al.  Quantitatively Assessing Roads Extracted from High-Resolution Imagery , 2004 .

[18]  George Vosselman,et al.  Road tracing by profile matching and Kaiman filtering , 1995 .

[19]  Thierry Toutin,et al.  Linear planimetric feature domains modeling for multisensor fusion in remote sensing , 2000, SPIE Defense + Commercial Sensing.

[20]  Lindi J. Quackenbush.  A Review of Techniques for Extracting Linear Features from Imagery , 2004 .

[21]  Kyung-Ok Kim,et al.  Tracking Road Centerlines from High Resolution Remote Sensing Images by Least Squares Correlation Matching , 2004 .

[22]  José A. Malpica,et al.  An automatic method for road extraction in rural and semi-urban areas starting from high resolution satellite imagery , 2005, Pattern Recognit. Lett..

[23]  Zuxun Zhang,et al.  A Robust Method for Semi-Automatic Extraction of Road Centerlines Using a Piecewise Parabolic Model and Least Square Template Matching , 2004 .

[24]  Mehdi Mokhtarzade,et al.  Road detection from high-resolution satellite images using artificial neural networks , 2007, Int. J. Appl. Earth Obs. Geoinformation.