Abstract
Content based image retrieval system (CBIR) retrieves images from a database based on the contents of the query image.Retrieval based on the shape of the 2D object present in the image is important in several applications. Shape of an objectis invariant to translation, scaling, rotation and mirror-reflection. Hence, the representation scheme which possesses all theseproperties is important. Signature histogram and k th order augmented histogram have all invariance properties [17]. But,they are applicable only to convex shapes. This representation scheme assumes that centroid to contour distance is a functionof angle (with a predefined axis). This is not true for non-convex and open shapes, since for some angles there can be more than onecentroid to contour distance. The current paper does not make this assumption, but considers distribution of centroid tocontour distances. Further, to reduce the false positive rate, distribution of local variations of the centroid contour distancesare also considered. Experimental studies are done using a standard image database and handwritten symbols database. The present technique is comparedagainst a similar recent technique.
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Gokaramaiah, T., Viswanath, P., Eswara Reddy, B. (2011). A Shape Representation Scheme for 2D Images Using Distributions of Centroid Contour Distances and Their Local Variations. In: Das, V.V., Thankachan, N. (eds) Computational Intelligence and Information Technology. CIIT 2011. Communications in Computer and Information Science, vol 250. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25734-6_81
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DOI: https://doi.org/10.1007/978-3-642-25734-6_81
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