Open AccessIndian topographical map symbols understanding system
Author(s) -
Ganpatrao Nikam Gitanjali,
Ghosh Jayanta Kumar
Publication year - 2015
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2013.0311
Subject(s) - artificial intelligence , computer science , pattern recognition (psychology) , symbol (formal) , similarity (geometry) , representation (politics) , set (abstract data type) , computer vision , image (mathematics) , politics , political science , law , programming language
Symbol understanding is a pre‐requisite for reading and interpretation of any map. Thus, any topographic map‐based automated system needs to understand generic symbols associated with the set of maps. The objective of this study was to develop an automated system for the understanding of Survey of India topographic map symbols. The system has been developed making use of shape analysis adopting a complex‐valued chain coding method for representation of the (exterior) boundary of the symbol. Fourier discrete transform and autocorrelation function have been used for shape descriptions. Classification and recognition have been implemented through a template matching method based on similarity measures. The system has been trained with 150 samples of 20 Indian topographic symbols and tested for 200 samples of each of the 20 symbols extracted from sample maps. Experimental results showed that the proposed method has an overall recognition rate of 84.68% as well as the improved mean average precision of symbol recognition. However, understanding of interconnected and/or crowded symbols may be taken up as future scope of this work.