Vol15 No.7: 1460-1470
【Title】An improved Mahalanobis distance-based colour segmentation method for rural building recognition
【Author】XIE Jia-li1*; LI Yong-shu1; CAI Guo-lin1*; WANG Feng1; LI He-chao2
【Addresses】1 Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China; 2 Center of Land Acquisition and Consolidation in Sichuan Province, Chengdu 610041, China
【Corresponding author】XIE Jia-li
【Citation】Xie JL, Li YS, Cai GL, et al. (2018) An improved Mahalanobis distance-based colour segmentation method for rural building recognition. Journal of Mountain Science 15(7). https://doi.org/10.1007/s11629-017-4669-4
【Abstract】Aiming at the rapid identification of rural buildings in complex environments from high-spatial-resolution images, an improved Mahalanobis distance colour segmentation method (IMDCSM) is proposed and realised in Red, Green and Blue (RGB) space. Vector sets of a lower discrete degree are obtained by filtering the colour vector sets of the building samples, and a standard ellipsoid equation can be constructed based on these vector sets. The threshold of interested colour range can be flexibly and intuitively selected by changing the shape and size of this ellipsoid. Then, according to the relationship between the location of the image pixel colour vector and the ellipsoid, all building information can be extracted quickly. To verify the effectiveness of the proposed method, unmanned aerial vehicle (UAV) images of two areas in the suburbs of Chengdu city and Deyang city were utilised as experimental data for image segmentation, and the existing colour segmentation method based on the Mahalanobis distance was selected as an indicator to assess the effectiveness of this method. The experimental results demonstrate that the completeness and correctness of this method reached 95% and 83.0%, respectively, values that are higher than those of the Mahalanobis distance colour segmentation method (MDCSM). In general, this method is suitable for the rapid extraction of rural building information, and provides a new threshold selection method for classification.
【Keywords】Mahalanobis distance; Red, Green and Blue vector; Colour image segmentation; Rural buildings recognition