The Method of Normalization to Determine Invariants
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape measures for content based image retrieval: a comparison
Information Processing and Management: an International Journal
Automatic Document Logo Detection
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
An experimental comparison of seven shape descriptors in the general shape analysis problem
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part I
An efficient color representation for image retrieval
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
Application of 2D fourier descriptors and similarity measures to the general shape analysis problem
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
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The main purpose of the paper is to present a method of detection, localization and segmentation of stamps (imprints) in the scanned document. It is a very actual topic these days since more and more traditional paper documents are being scanned and stored on digital media. Such digital copy of a stamp may be then used to print a falsified copy of another document. Thus, an electronic version of paper document stored on a hard drive can be taken as a forensic evidence of possible crime. The process of automatic image retrieval on a basis of stamp identification can make the process of crime investigation more efficient. The problem is not trivial since there is no such thing like stamp standard. There are many variations in size, shape, complexity and ink color. It should be remembered that the scanned document may be degraded in quality and the stamp can be placed on relatively complicated background. The algorithm consists of several steps: color segmentation and pixel classification, regular shapes detection, candidates segmentation and verification. The paper includes also some results of selected experiments on real documents having different types of stamps.