Extracting residential areas from historical raster topographic maps benefits to analyze land type change. The existing algorithms have the shortcomings including easily misidentifying objects and low positional accuracy of the identified boundary, so we have presented a new automatic recognition method based on Gabor filter for extracting residential areas from historical raster topographic maps. First, the method detected the hatched areas using Gabor filter, Gaussian smoothing, binarization, erosion, and an operation. Afterward, an endpoint of a hatched line on the top of the hatched areas was taken as the starting point, then tracing a boundary point of the residential area along a hatched line toward northeast 45 degrees direction using dynamic filling strategy. Second, an adjacent boundary point was traced according to the pixel value relation of eight neighborhoods by taking the first found boundary point as a starting point. In the tracking process, removing the noises using the pixel value relation of the neighboring pixels and the designed strip detector. Ultimately, the residential boundary was obtained. The experiments were carried out on the samples of three typical areas. The results showed that our method was effective and practical, and outperformed the previous methods in integrity and positional accuracy of the residential boundary.
Bibliographical noteFunding Information:
This work was supported in part by the National Natural Science Foundation of China (NSFC) Projects under Grant 41201409, Grant 41561084, and Grant 41661083, in part by the scholarship from the China Scholarship Council (CSC) under Grant 201409470010, in part by the China Postdoctoral Science Foundation under Grant 2018M632991, and in part by the Open Foundation of Key Laboratory for National Geography State Monitoring (National Administration of Surveying, Mapping and Geoinformation) under Project 2016NGCM01 and Project 2016NGCM07.
© 2013 IEEE.
- data mining
- Gabor filter
- image processing
- raster map
- Residential areas recognition