Polyline curvatures based robust vector data hashing

Suk‐Hwan Lee

doi:10.1007/s11042-013-1661-z

Polyline curvatures based robust vector data hashing

2013-08-31

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AI

DOI：10.1007/s11042-013-1661-z

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Abstract

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The growth in applications for vector data such as CAD design drawings and GIS digital maps has increased the requirements for authentication, copy detection, and retrieval of vector data. Vector data hashing is one of the main techniques for meeting these requirements. Its design must be robust, secure, and unique, which is similar to image or video hashing. This paper presents a vector data hashing method based on the polyline curvature for design drawings and digital maps. Our hashing method extracts the feature values by projecting the polyline curvatures, which are obtained from groups of vector data using GMM clustering, onto random values, before generating the final binary hash by binarization. A robustness evaluation showed that our hashingmethod had a very low false detection probability during geometrical modifications, rearrangements, and similar transformations of objects and layers. A security evaluation based on differential entropy showed that the level of uncertainty was very high with our hashing method. Furthermore, a uniqueness evaluation showed that the Hamming distances between hashes were very low.

Keywords:

Vector data model

Content hashing

Authentication

Copy detection

Design drawing

Digital map

Polyline curvatures based robust vector data hashing

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