Direction estimation using square lattice and cadastral map assembling

Yusuke Takahashi, Liu Fei, Wataru Ohyama, Tetsushi Wakabayashi, Pumitaka Kimura

Research output: Contribution to journalArticlepeer-review


This paper proposes a technique for direction estimation by means of square grid points in order to improve the performance of cadastral map assembling technique based on Merlin-Farber (MF) algorithm. The MF algorithm requires direction normalization of the segments (of cadastral map) preceding the assembling. Proposed direction estimation technique is based on the spatial frequency analysis of autocorrelation by MF algorithm for the square rid points regularly drawn with constant intervals on the segments. Since many square grid points are drawn over entire area of the segments the direction can be estimated more accurately with those points when compared the direction is estimated with single north arrow. To assemble two adjacent segments the longest common boundary is detected by MF algorithm. Evaluation experiments are performed to compare the accuracy and the success rate of map assembling when the direction is estimated and normalized based on the square grid points and when estimated and normalized based on the north arrow. Total of 324 map segments of 47 district provided by Institut Geographique National France are used in the experiments. While the map assembling based on the north arrow tends to form inaccurate cadastral maps the proposed technique assembles the map more accurately. The results of experiments shows that the proposed technique achieves sufficient success rate and accuracy so that it effectively reduces the labor cost and time of the cadastral map assembling.

Original languageEnglish
Pages (from-to)2150-2158+8
JournalIEEJ Transactions on Electronics, Information and Systems
Issue number12
Publication statusPublished - 2010
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


Dive into the research topics of 'Direction estimation using square lattice and cadastral map assembling'. Together they form a unique fingerprint.

Cite this