A rotation and scale invariant approach for multi-oriented floor plan image retrieval

Article Type

Research Article

Publication Title

Pattern Recognition Letters

Abstract

An automatic system for analysis and retrieval of building floor plans images is helpful for the architects while designing new projects and providing recommendations to the buyers. For such systems, query by example is preferred over query by keyword, for which user's requirements must be available in digital image form. Floor plans are converted to digital form by scanning and often get rotated slightly by a certain degree of angle during digitization. In this paper, we have proposed a geometric feature-based approach for floor plan image retrieval and our key contribution is to handle different kinds of rotation and scale while retrieving similar floor plan from the database. Our framework is divided into three phases, namely outer shape feature extraction, internal object feature extraction, followed by matching and retrieval. For our experimentation, we have rotated images of ROBIN dataset as currently no rotated floor plan dataset was available. Our experiment shows that the proposed methodology outperforms recent competing methods.

First Page

1

Last Page

7

DOI

10.1016/j.patrec.2021.01.020

Publication Date

5-1-2021

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