TY - GEN
T1 - Linear Elements Separation via Vision System Feature and Seed Spreading from Topographic Maps
AU - Xie, Fei
AU - Zhang, Yanning
AU - Guo, Xinming
AU - Zhang, Wei
AU - Zhou, Zhaoyong
AU - Xu, Pengfei
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/11
Y1 - 2020/11
N2 - In topographic maps, It is difficult to separate the linear elements, including contour lines, roads, latitude and longitude lines from complicated background due to the pixels with aliasing and false colors, and there exists some background in the result images extracted by the existing methods, especially when the color and energy of linear elements and background are similar in some particular maps, or the maps have low contrast contour lines. To solve these problems, this paper introduces the idea of seed spreading, and puts forward a novel method for separating linear elements. In this method, all the seeds carry the color information of the pixels and the energy information in the negative grayscale images, and they can search other pixels as their brothers to be combined into seed groups according to the color and energy similarity. The seeds have good perception of the environment around them, and the shapes of the seed groups are variable. Furthermore, the seeds are determined as linear elements by analyzing the color and energy differences between the seed groups and the areas around them. The experimental results show that our method can distinguish linear elements from the background more accurately than the previous methods.
AB - In topographic maps, It is difficult to separate the linear elements, including contour lines, roads, latitude and longitude lines from complicated background due to the pixels with aliasing and false colors, and there exists some background in the result images extracted by the existing methods, especially when the color and energy of linear elements and background are similar in some particular maps, or the maps have low contrast contour lines. To solve these problems, this paper introduces the idea of seed spreading, and puts forward a novel method for separating linear elements. In this method, all the seeds carry the color information of the pixels and the energy information in the negative grayscale images, and they can search other pixels as their brothers to be combined into seed groups according to the color and energy similarity. The seeds have good perception of the environment around them, and the shapes of the seed groups are variable. Furthermore, the seeds are determined as linear elements by analyzing the color and energy differences between the seed groups and the areas around them. The experimental results show that our method can distinguish linear elements from the background more accurately than the previous methods.
KW - color information
KW - energy density
KW - linear elements
KW - seed groups
KW - seed spreading
UR - http://www.scopus.com/inward/record.url?scp=85105267699&partnerID=8YFLogxK
U2 - 10.1109/CIS52066.2020.00011
DO - 10.1109/CIS52066.2020.00011
M3 - 会议稿件
AN - SCOPUS:85105267699
T3 - Proceedings - 2020 16th International Conference on Computational Intelligence and Security, CIS 2020
SP - 11
EP - 15
BT - Proceedings - 2020 16th International Conference on Computational Intelligence and Security, CIS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th International Conference on Computational Intelligence and Security, CIS 2020
Y2 - 27 November 2020 through 30 November 2020
ER -