|Author||Rajeswari, M. ♦ Gurumurthy, K. S. ♦ Reddy, L. Pratap ♦ Omkar, S. N. ♦ Senthilnath, J.|
|Subject Domain (in DDC)||Computer science, information & general works ♦ Data processing & computer science|
|Subject Keyword||Normalized Cut ♦ Level Set ♦ Automatic Road Extraction ♦ Mean Shift Method ♦ Satellite Imagery ♦ Reference Data ♦ Urban Population ♦ Last Decade ♦ High Resolution Satellite Image ♦ Hence Automatic Extraction ♦ Geographic Information ♦ Time-consuming Task ♦ Urban Planning ♦ Urban Planner ♦ Building Etc ♦ Keywords Road Extraction ♦ Manual Extraction ♦ Planning Official ♦ Mean Shift Algorithm ♦ High Resolution ♦ Performance Evaluation ♦ Ever-changing Urban Environment ♦ Important Feature ♦ Urban Development|
|Abstract||The Urban population is growing so fast in India that planning officials are racing to keep up with urban development.Use of geographic information like satellite imagery helps urban planners manage the ever-changing urban environment accurately and efficiently. Roads are one of the most important features to be extracted from Satellite imagery for urban planning. Manual extraction of roads is operator dependent and time-consuming task. Hence Automatic extraction of roads from high resolution satellite images has grown in importance in the last decade. An approach for automatic road extraction from high resolution based on Level set, Normalized Cuts and Mean Shift algorithms is developed. Initially the image is preprocessed to improve the tolerance by reducing the noises (buildings etc.,) then roads are extracted based on the three methods. Finally the comparison of accuracy of automatic road extraction of three methods is quantitatively assessed with manually extracted reference data. Keywords- Road extraction; Level Set; Mean Shift method; Normalized cuts; Performance evaluation;|
|Educational Role||Student ♦ Teacher|
|Age Range||above 22 year|
|Education Level||UG and PG ♦ Career/Technical Study|
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