Abstract-Effective image retrieval by content from database requires that visual image properties are used instead of textual labels to properly index and recover pictorial data. Retrieval by shape similarity, given a user-sketched template is particularly challenging, owing to the difficulty to derive a similarity measure that closely conforms to the common perception of similarity by humans. In this paper, we present a technique which is based on elastic matching of sketched templates over the shapes in the images to evaluate similarity ranks. The degree of matching achieved and the elastic deformation energy spent by the sketch to achieve such a match are used to derive a measure of similarity between the sketch and the images in the database and to rank images to be displayed. The elastic matching is integrated with arrangements to provide scale invariance and take into account spatial relationships between objects in multi-object queries. Examples from a prototype system are expounded with considerations about the effectiveness of the approach and comparative performance analysis. Index Terms-Image database, image retrieval by sketch, shape similarity-based retrieval, elastic matching.
A representative work in REF models users' sketches as closed silhouettes and matches them to the edges in the image using a similarity measure defined by the degree of matching and the elastic deformation energy.
Image Retrieval by Elastic Matching of User Sketches
ICIAP
Computer Science