Sketch-Based Image Retrieval by Size-Adaptive and Noise-Robust Feature Description

Abstract

We review available methods for Sketch-Based Image Retrieval (SBIR) and we discuss their limitations. Then, we present two SBIR algorithms: The first algorithm extracts shape features by using support regions calculated for each sketch point, and the second algorithm adapts the Shape Context descriptor to make it scale invariant and enhances its performance in presence of noise. Both algorithms share the property of calculating the feature extraction window according to the sketch size. Experiments and comparative evaluation with state-of-the-art methods show that the proposed algorithms are competitive in distinctiveness capability and robust against noise.