Similarity analysis for shape retrieval by example

This work proposes a query-by-example algorithm for shape retrieval from a color image database. The main contribution of this work is an unified approach for shape matching and similarity ranking using a modal representation. Prior work mostly performed point correspondence determination and similarity ranking of shapes in two distinct steps or performed one of them. We define a new shape-similarity metric and attempt to address the question how similar two shapes in an image database are, which currently is an important problem in shape-based retrieval systems. Unlike most reported methods, the presented approach does not require extraction of connected boundaries or silhouettes. It is rotation-, and scale-invariant, and can handle mild deformations of objects. The results are promising for using the algorithm in the context of database query by image content.