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Information extraction from topographic map using colour and shape analysis

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Abstract

The work presented in this paper is related to symbols and toponym understanding with application to scanned Indian topographic maps. The proposed algorithm deals with colour layer separation of enhanced topographic map using k-means colour segmentation followed by outline detection and chaining, respectively. Outline detection is performed through linear filtering using canny edge detector. Outline is then encoded in a Freeman way, the x-y offsets have been used to obtain a complex representation of outlines. Final matching of shapes is done by computing Fourier descriptors from the chain-codes; comparison of descriptors having same colour index is embedded in a normalized scalar product of descriptors. As this matching process is not rotation invariant (starting point selection), an interrelation function has been proposed to make the method shifting invariant. The recognition rates of symbols, letters and numbers are 84.68, 91.73 and 92.19%, respectively. The core contribution is dedicated to a shape analysis method based on contouring and Fourier descriptors. To improve recognition rate, obtaining most optimal segmentation solution for complex topographic map will be the future scope of work.

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  1. Geomatics Engineering Group, Civil Engineering Department, Indian Institute of Technology, Roorkee, 247 667, India

    NIKAM GITANJALI GANPATRAO & JAYANTA KUMAR GHOSH

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  1. NIKAM GITANJALI GANPATRAO
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  2. JAYANTA KUMAR GHOSH
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Correspondence to NIKAM GITANJALI GANPATRAO.

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GANPATRAO, N.G., GHOSH, J.K. Information extraction from topographic map using colour and shape analysis. Sadhana 39, 1095–1117 (2014). https://doi.org/10.1007/s12046-014-0270-5

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