Abstract. Analysis of intrinsic symmetries of non-rigid and articulated shapes is an important problem in pattern recognition with numerous applications ranging from medicine to computational aesthetics. Considering articulated planar shapes as closed curves, we show how to represent their extrinsic and intrinsic symmetries as self-similarities of local descriptor sequences, which in turn have simple interpretation in the frequency domain. The problem of symmetry detection and analysis thus boils down to analysis of descriptor sequence patterns. For that purpose, we show two efficient computational methods: one based on Fourier analysis, and another on dynamic programming. Metaphorically, the later can be compared to finding palindromes in text sequences.
Detection of text embedded in images and videos is very useful in applications like indexing and retrieval of multimedia content. There exist very few techniques which can differentiate between overlay text which is embedded artificially and scene text which occurs naturally in images. This paper proposes an efficient method for detection and localization of overlay text from still images. By using colour filter array(CFA)-based forgery localization method, the proposed technique successfully removes any scene text present in the image. Experimental results on a database of 315 images demonstrate the efficiency of the proposed method.
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