Connected component-based technique for automatic extraction of road centerline in high resolution satellite images

被引:61
|
作者
Sujatha, Chinnathevar [1 ]
Selvathi, Dharmar [2 ]
机构
[1] Sethu Inst Technol, Dept Elect & Commun Engn, Kariapatti 626115, Tamil Nadu, India
[2] Mepco Schlenk Engn Coll, Dept Elect & Commun Engn, Sivakasi 626005, Tamil Nadu, India
关键词
Road extraction; High resolution satellite image; Connected component; Morphological operation; Trivial opening; Completeness; Correctness; Quality; MATHEMATICAL MORPHOLOGY; NETWORK EXTRACTION; SHAPE-FEATURES; CLASSIFICATION; TRACKING;
D O I
10.1186/s13640-015-0062-9
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In remote sensing analysis, automatic extraction of road network from satellite or aerial images can be a most needed approach for efficient road database creation, refinement, and updating. In this paper, a method for automatic extraction of road centerline from high resolution satellite image is proposed. The proposed work consists of three stages: segmentation of road region, connected component-based operations used to extract the connected road component from segmented road region, and removal of unwanted non-road pixels using morphological operation. The proposed algorithm is implemented on various satellite images, and the results are given in this work. The performance of the proposed method is evaluated by comparing the results with ground truth road map as reference data, and performance measures such as completeness, correctness, and quality are calculated. The average value of completeness, correctness, and quality of various images are 90%, 96%, and 87%, respectively. These measures prove that the proposed work yields road network very closer to reference road map. The proposed method yields very good result for noisy image also, and it proved that the proposed method is insensitive for noise. Performance measures of the proposed work are compared with other methods, and this comparison proves that the proposed method yields very good results than other methods.
引用
收藏
页数:16
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