An Alphabetic Contour-Based Descriptor for Shape-Based Image Retrieval

Content-based image retrieval methods use color, texture and shape of an object for indexing and retrieval. Among these features, shape is a basic visual feature that holds significant information of the object. In this paper an alphabetic contour-based shape description method is proposed to facilitate shape classification and retrieval. The proposed method breaks down shape's contour into small segments and assigns unique alphabetic symbol for each segment based on its geometrical features. These symbols are used to create feature string which we call it, an alphabet string. The alphabet strings are compared together using dynamic programming during classification. The proposed method was tested on BROWN dataset that consists of occluded, articulated and missing part shapes. Results show the feasibility of the method and highlight its advantages over some state-of-the art methods.